Persuasion within Advertising: Metaphorical Expressions vs. Literal Expressions
Metaphor literal persuasion advertising marketing figurative language emotion
The present research built upon research conducted by Citron and Goldberg (2014) on figurative language, emotion, and the brain. This study examined the three different data sets: sentences, stories and sentences with taste metaphors collected by Citron and Goldberg (2014). It examined three different data sets: sentences, stories and sentences with taste metaphors. Metaphorical and literal sentences, stories and taste metaphors were rated on emotional valence, imageability, emotional arousal, metaphoricity and similarity in meaning. Familiarity was rated within sentences and taste metaphors and understandability and naturalness were rated within stories. This study explored relationships among variables, relationships between metaphors and literal counterparts, relationships between each data set and lastly, relationships between each data set when split by type: metaphor and literal. Findings from this investigation provide evidence for marketers, of the benefits of using metaphors within advertising to increase persuasion and consumer buying behaviour. A company who wants to portray imagination, develop images within a consumer’s mind and evoke emotional arousal should use metaphorical sentences within their advertisements. Additionally, the more arousing a sentence the more imaginable, therefore, marketers should specifically employ emotionally arousing material to further engage a consumer. This study can add to literature on figurative language and persuasion. Also, provide evidence for marketers who want to increase their sales and further persuade consumers with an effective approach
All metaphorical sentences and stories were created in German with words that would obtain a metaphorical interpretation. Then each word was replaced with its literal counterpart, which created: one hundred and twenty non-taste related sentences, sixty metaphorical “The bride was very moved by her wedding” and sixty literal “The bride was very happy about her wedding”. Sixty-four stories, thirty-two metaphorical “Lisa was sitting in her physics class and was still digesting the stuff from the lesson before when her teacher announced a task to bite your teeth out on.” and thirty-two literal “Lisa was sitting in her physics class and was still having problems with the stuff from the lesson before when her teacher announced a really difficult task.” Finally, seventy-four taste metaphors, thirty-seven metaphorical “She received a sweet compliment” and thirty-seven literal “She received a nice compliment”. Specific instructions were created by Francesca Citron for each variable to be rated (See Appendix A). Sentences, stories and taste metaphors were rated on emotional valence, imageability, emotional arousal, metaphoricity and similarity in meaning. Emotional Valence refers to how positive or negative the stimulus is which was rated on a scale from -3 (very negative) to + 3 (very positive) through 0 (neutral). All other variables were measured on a scale of 1 to 7. Imageability is the ability to evoke a mental picture rated: 1 “not imaginable at all” and 7 “very imaginable”. Emotional arousal describes to what extent the stimulus is emotionally stimulating rated: 1 “not intense at all” and 7 “very intense”. Metaphoricity describes the figurativeness of the stimulus rated: 1 “literal” and 7 “very metaphorical”. Lastly, similarity in meaning which refers to how similar the meaning of both metaphorical and literal counterparts are with regard to contents. For instance, the metaphorical sentence “He praised her to the skies” compared to the literal sentence “He praised her fulsomely”. These have the same meaning, thus the meaning similarity between metaphorical and literal sentence is high. This was rated 1 “not similar at all” and 7 “very similar/equal in meaning”. Familiarity was rated within sentences and taste metaphors, which describes how familiar the stimulus is rated: 1 “not familiar at all” and 7 “very familiar”. Additionally, taste relatedness was measured for taste metaphors which refers to the extent a sentence is associated with degustation. It was rated as 1 “not taste-related at all” and 7 “very taste-related”. Lastly, understandability and naturalness were rated within stories. Understandability is about the easiness of grasping what the content means rated: 1 “very difficult to understand” and 7 “very easy to understand”. Naturalness is how normal and daily a story or its parts are rated: 1 “not natural at all” and 7 “very natural”. To evaluate complexity, several measurable parameters were created. For each parameter one “complexity point” was given, therefore, creating one overall complexity score. For all data sets all 9 characteristics were the same: subordinate clauses, relative clauses, passive forms, compound nouns, appearing persons, adverbs and adverbial phrases, conjunctive forms, analytically-formed tenses/infinitive constructions and marked/deviating structure of sentence. For sentences and taste metaphors alone the number of words was also a characteristic and within stories the number of metaphors. (See Appendix B). Procedure Participants were each provided with a consent form to sign if they agreed to partake in the study. Once completed, participants were provided with a URL via E-mail to access the questionnaire. General instructions were shown first, followed by the specific instructions for the first variable to be rated. The words were then presented, each one at the centre of the page immediately followed by the 7-point scale. When all words had been rated for one variable, instructions for the next variable rating appeared. The order of variables were random for each participant. This procedure was the same for all sentences, stories and taste metaphors. Data Analysis All the means and standard deviations were calculated and used for the analyses for all sentences, stories and taste metaphors. Independent sample t-tests were then used to look at the differences between metaphors and literal counterparts of each variable within the three data sets. When there was a specific hypothesis a one tailed t-test was implemented however, when there was no hypothesis a two tailed t-test was applied. Next, the variable emotional valenced squared was computed to represent the quadratic relationship between all other variables and then used within the following data analyses. Firstly, a multiple regression was then used to analyse any quadratic or linear relationships between emotional valence and other variables within each data set. In each regression, features of no interest were partialled out by entering them as predictors in the first step; then valence and valence squared entered in the second step. Additionally, partial correlations were conducted within each data set to look at linear relationships between pairs of variables within metaphors and literal counterparts by controlling for other variables. Lastly two types of analyses of variances were conducted, firstly, one-way between subjects ANOVAs to look at the difference between datasets: sentences, stories and taste and their impact on emotional arousal, imageability, emotional valence and metaphoricity. Then one-way between subjects ANOVAs to look at the differences between datasets when split by type, metaphors and literal counterparts and their impact upon variables.
The rating data had been gathered already by Francesca Citron during her research in Berlin and ethical approval had been obtained at that time. The present study has been approved by the Department’s Research Ethics committee at Lancaster University.
An investigation into the effect of climatic, ambient temperature on societal-level income inequality
Previous research has revealed contradictory findings concerning the relationship between temperature and behaviour. Some studies have found a warmer-is-better effect; warmer temperatures are associated with enhanced interpersonal interactions, including pro-social behaviours. Whereas other studies have found a warmer-is-worse effect; warmer temperatures are associated with negative social behaviours such as conflict, societal instability, crime and aggressive behaviours. The present study investigated the relationship between climatic, ambient temperature and societal income inequality. Climatic temperatures and Gini ratios (a measure of income inequality) were sourced from online databases for 29 countries across a range of time periods that fell between 1961 and 2015. A panel linear model analysis revealed that climatic temperature had no direct effect, nor lagged effect on income inequality. Therefore, the findings are not congruent with the warmer-is-better literature or the warmer-is-worse literature. Despite the null effect, the present study provides a further data point towards the debate concerning the effect of temperature on behaviour.
Firstly, the study required Gini ratios of disposable, equivilsed income. The Gini ratio is a measure of income inequality whereby a ratio of 1 reflects perfect inequality (i.e. one household receives all of the income) and a ratio of 0 is indicative of perfect equality (i.e. income is equally shared across households). The ratio was calculated from disposable income, which is income after the deduction of taxes and social security charges. Additionally the ratio was equivilised which means that the ratio was adjusted to account for different sizes and compositions of households. Secondly, the study required mean climatic temperatures in degrees celsius. Procedure Gini ratios for 29 countries belonging to the organisation for economic co-operation and development (OECD) were sourced from several online databases that had calculated the ratios. The countries and years used in the present analysis were somewhat dictated by the availability of Gini ratios online and as a result the OECD countries Australia, Chile, Israel, Japan, Korea and Mexico could not be included in the present analysis and the year ranges included fell between 1961-2015. See table 1 for the sources of Gini ratios, and the countries and years for which Gini ratios were available. It is important to note that the surveys from which the Gini ratios were calculated were slightly different, for example, some had different definitions of a ‘household’. Additionally, not all of the sources provided the exact Gini ratio calculation used. Table 1: Online sources from which Gini ratios were obtained from several countries across several, differing, time periods Country Time period Source of Gini ratios Austria (AUT) 1995-2001, 2003-2015 Eurostat, European Union Statistics on Income and Living Conditions (2017). Belgium (BEL) 1995-2001, 2003-2015 See Austria. Canada (CAN) 1976-2015 Statistics Canada (2017). Czechoslovakia (CZE) 2001, 2005-2015 See Austria. Denmark (DEN) 1987-2015 Statistics Denmark (2017). Estonia (EST) 2000-2002, 2004-2015 See Austria. Finland (FIN) 1987-2014 OECD Data (2017) France (FRA) 1995-2002, 2004-2015 See Austria. Germany (GER) 1984-2013 German Socio-economic Panel Study (2015) Greece (GRE) 1995-2001, 2003-2015 See Austria. Hungary (HUN) 2000-2002, 2005-2015 See Austria. Iceland (ISL) 2004-2015 See Austria. Ireland (IRL) 1995-2001, 2003-2015 See Austria. Italy (ITA) 1995-2001, 2004-2015 See Austria. Latvia (LVA) 2000, 2005-2015 See Austria. Luxembourg (LUX) 1995-2001, 2003-2015 See Austria. Netherlands (NED) 2000-2014 Netherlands Central Bureau of Statistics (2017) New Zealand (NZL) 1984, 1988, 1990, 1992, 1994, 1996, 1998, 2001, 2004, 2007, 2009-2014 Perry (2016) Norway (NOR) 1986-2015 Statistics Norway (2017). Poland (POL) 2001, 2005-2015 See Austria. Portugal (POR) 1995-2001, 2004-2015 See Austria. Slovakia (SVK) 2005-2015 See Austria. Slovenia (SVN) 2000-2002, 2005-2015 See Austria. Spain (ESP) 1995-2002, 2004-2015 See Austria. Sweden (SWE) 1975, 1978-2013 Statistics Sweden (2017). Switzerland (SWI) 2007-2015 See Austria. Turkey (TUR) 2002, 2006-2013 See Austria. United Kingdom (UK) 1961-2014 Institute for fiscal studies (2016) United States (USA) 1967-2013 Proctor, Semega & Kollar, M. A. (2016). Temperatures were sourced from the Climate Change and Knowledge Portal (2017) which contained the mean temperatures in degrees celsius for every country that was included in the present analysis for each month from years 1901-2015. Because we obtained mean Gini ratios for each year, we calculated mean climatic temperatures by calculating the average of the 12 months for each year, and country, that a Gini ratio was obtained. All Gini ratios and temperatures were accessed on 28th June 2017. Design and analysis In the present study the predictor variable was temperature and the outcome variable was Gini ratios. Data was collected for 29 countries across differing time periods ranging from 8-53 years resulting in a dataset with 594 observations. The dataset was a panel dataset whereby the data was cross-sectional (i.e. across countries) and longitudinal (i.e. across time periods) and unbalanced because of the differing time periods for each country. Therefore, to analyse the effect of temperature on Gini ratios, the plm package (Croissant & Millo, 2008) in R (R development core team, 2012) was used because this analysis has been designed to account for panel, unbalanced datasets. Additionally this package could determine whether country and time had an effect on Gini ratios and how these effects should be accounted for. The general linear model for the data set was (Croissant & Millo, 2008): yit = α + Txit + µi + t + it i = country t = time yit = Gini ratios α = intercept Txit the coefficient of the effect of temperature on Gini ratios µi = the unobserved error as a result of the effect of country on Gini ratios t = the unobserved error as a result of the effect of time on Gini ratios it = residual/idiosyncratic error, independent of the predictor and individual error components The specific model that was used in the present analysis was dependent on the existence of country effects (i.e. µi) and time effects (i.e.t) and the nature of these effects. There are three potential ways to model the panel datasets when estimating the effect of temperature on Gini ratios (Croissant & Millo, 2008): 1 – Pooled model; where time and country have no effect on Gini ratios (i.e. µi =0, t =0). Thus, the pooled models estimation is consistent and efficient, and applies across countries and time. 2 – Fixed effects model; where there are effects of country and/or time on Gini ratios and these effect(s) are correlated with the predictor variable, temperature. These correlated effect(s) result in the pooled models’ estimation being inconsistent because the estimates differ across countries and/or across time. Therefore, the fixed effects model accounts for the heterogeneity between countries and/or time by treating country and/or time as parameters to be estimated in the model and consequently the model gives consistent estimates of the effect of temperature on Gini ratios. This model can be one-way (i.e. the effect of country or time are taken into account) or two-way (i.e. the effects of country and time are taken into account). 3 – Random effects model; where there are effects of country and/or time on Gini ratios and these effect(s) are uncorrelated with the predictor variable, temperature. As a consequence of these uncorrelated effects, although the pooled models estimation is consistent, this estimation is inefficient. Thus, the random effects model accounts for the heterogeneity between countries and/or time by treating country and/or time as a separate error component(s) in the model and consequently the model gives consistent and efficient estimates of the effect of temperature on Gini ratios. Similar to the fixed effects model, the random effects model can be one-way or two-way. To determine which model was appropriate for the dataset, and thus to determine the nature of the effects of country and time, we performed exploratory (i.e. graphical representations) and confirmatory (i.e. hypothesis testing) analyses. Firstly, we used graphs to visualise whether the intercepts were heterogeneous across countries and time as heterogeneity would suggest that the pooled model (i.e. model 1) was not appropriate. Following this, to determine whether the pooled model was appropriate for the dataset, we used the F test of stability, which by default tests whether the same coefficients applied to each country. Following this F test there were two potential routes. (i) If the analysis revealed that the same coefficients applied across countries, we would then implement an F test of stability to test whether the same coefficients applied across time. If the second F test revealed that the same coefficients applied across time, a pooled model (i.e. model 1) would be used as this would provide a consistent and efficient estimation. Whereas if the second F test revealed that the coefficients did not apply across time, this would suggest that the pooled model was not appropriate and thus a Hausman test would be required to determine whether time should be modelled as a fixed effect (i.e. one-way fixed effects model; model 2) or random effect (i.e. a one-way random effects model; model 3). (ii) If the analysis revealed that coefficients did not apply across countries this would suggest that a pooled model (i.e. model 1) was inappropriate for the dataset. Consequently a langrage multiplier test would be required to determine whether a one-way or two-way effects model should be used i.e. whether country alone had an effect on Gini ratios (i.e. one-way) or whether country and time had independent significant effects on Gini ratios (i.e. two-way). Secondly, a Hausman test would be necessary to determine whether the effect(s) should be modelled as fixed (i.e. fixed effects model; model 2) or random (i.e. random effects model; model 3). Once a model had been specified, we estimated the direct and lagged effect of temperature on Gini ratios. Finally, we carried out diagnostic testing to analyse whether there was serial correlation or cross-sectional independence in the idiosyncratic errors of the model that would need to be dealt with.
Does the use of prompts in shared reading facilitate the quantity and quality of language in Down Syndrome children?
Down syndrome, linguistic abilities, dialogic reading, prompted reading.
Children with Down syndrome typically present with specific linguistic and communicative difficulties. The present study aims to explore how dialogic prompted reading facilitates better quality and quantity of language production in pre-school aged Down syndrome children. Research has demonstrated how reading interventions enhance typically developing children’s linguistic qualities, yet few studies have investigated the beneficial effects of dialogic prompted reading among Down syndrome children. Eight Down syndrome and 8 typically developing children completed two shared reading tasks with their mothers. One task involved reading a book containing a series of prompted questions, the other book contained no prompts. As predicted, prompted reading resulted in the development of more complex syntax, better vocabulary production and facilitated better responses accuracy to literal and inferential concepts, in Down syndrome children. In addition, the inclusion of prompts also increased parental scaffolding techniques for both diagnostic groups. The results from this study indicate that dialogic prompted reading does improve Down syndrome children’s qualitative and quantitative linguistic abilities and promotes better communication with parents during shared reading tasks. These findings highlight the educational significance of prompted dialogic reading as a highly beneficial intervention for developing an array of linguistic qualities in children with Down syndrome.
Participants A total of 16 children and their mothers took part in this study. Eight children with Down syndrome (DS: 4 female, 4 male, age range = 4.58 years to 6.75 years, Mage = 5.3 years) and 8 typically developing children (TD: 2 female, 6 male, age range = 3.9 years to 6.66 years, Mage = 5.1 years). This is a secondary data analysis study and all participants were previously recruited by the principle investigator and supervisor, Kate Cain. Video recordings of all child-parent reading dyads were made and were transcribed into written from. The Departmental Ethics Committee approved this study prior to the author receiving any video or transcribed data. Stimuli In this study, mothers were given two books to read with their children, ‘Mooncake’ and ‘Skyfire’ (Asch, 2014; 2014). Parents were asked to read both books as they normally would read at home with their child. One version of each book contained a series of 12 prompts which were inserted at specific points and parents where asked read them aloud as they went through the book (based on Van Kleek et al, 2006). Between both books there were a total of 24 prompts. For each book, prompts were evenly split between 4 sub-categories: picture labelling prompts “What is that? (pointing to Bear)”, vocabulary prompts “What does ‘hollow’ mean?”, inference prompts “ Why did Bear fall asleep?”, and general knowledge prompts “What else could Bear have used to stick the spoon to the arrow?”. The aim of the prompts was to encourage communication and scaffolding interactions between mothers and children when reading together. These books where specifically selected for multiple reasons: first, they have been successfully used in previous studies investigating linguistic impairments in pre-school aged children with language difficulties (Van Kleek et al 1997; 2006; Hammet, Van Kleek & Huberty, 2003). Second, the classic story-line of each book provides opportunities for children to follow a written and pictorial narrative, enhancing their visual perception skills, as well as being age suitable and cognitively stimulating for DS and TD children (Gibson 1996; Engevik et al 2016). Procedure and Design Parent/child reading dyads were separated into groups based on diagnosis, where DS children and their mothers formed the experimental group, and TD children and their mothers formed the control group. There were two conditions; typical ‘unprompted’ reading and prompted reading. All participants took part in all conditions. In the unprompted reading condition, parents were given one of the books, selected at random (i.e ‘mooncake’) and asked to read with their child as they would normally read at home. In the prompted reading condition, parents were given the other book (i.e ‘skyefire’) and asked to read with their child as they normally would at home, but to additionally ask the twelve prompts that were inserted into the book. Within each condition, the order in which each child/parent dyad read each book was counterbalanced, as well as the order of books being presented between diagnostic groups was counterbalanced. The experimental sessions were conducted either in a university lab or at the participants home, and was a record session. The researcher did not take part in reading sessions, and was there for recording purposes only. Each reading session was audio and video recorded, which was later transcribed in to written format using Microsoft Excel. The specific areas of language where coded for using the Excel written transcript and then inputted into SPSS for statistical analysis. Coding Categories Child and parent speech were coded for under the following categories: children’s production of language (length and syntax), children’s production of specific vocabulary types (nouns, verbs, adjectives, adverbs, affirmatives and fillers), parents use of questions (literal and inferential questioning styles), children’s language abilities in response to questions (literal and inferential), accuracy of children’s response to questions (literal and inferential), parental scaffolding techniques and children linguistic abilities in response to scaffolding techniques. This was done so the direct effects of prompted reading on a variety children’s language abilities could be primarily investigated, as well as assessing the effect prompted reading has on parental scaffolding techniques. Length and Syntax: total number of utterances, total number of words and mean length of utterances produced by children The total number of utterances produced by DS and TD children was coded for using a simple counting strategy, from the written transcripts in Microsoft Excel. Each sentence spoken by both groups of children, including singular words which posed as a sentence, were tallied to create the total number of utterances, between reading conditions. The total number of words was calculated by totalling every word in each utterance across both reading conditions, and the mean length of utterance was calculated by dividing by the total number of words by the total number of utterances each child spoke. Inaudible speech and vocalisations were not included in the coding, neither where onomatopoeic noises children made, such as ‘Zzzzz’ when pretending to be a bee, as they are representations of sound not speech. Onomatopoeic speech, for example ‘splash’ or ‘bang’ was included in the coding process as they are representations of speech. Additionally, speech where children were reading sections of the book alongside their mothers was excluded from the coding process, for the sole reason that reading alongside a parent does not represent language ability but reflects their reading ability. Each child had a score for the total number of utterances, total number of words and mean length of utterances produced for prompted and unprompted reading conditions, which were then inputted into statistical software SPSS. These factors represent the quantity element of language. Vocabulary Production: nouns, verbs, adjectives, adverbs, affirmatives and fillers Children’s vocabulary production was coded under six sub-categories: nouns, verbs, adjectives, adverbs, affirmatives and fillers. These specific categories were chosen as previous research investigating vocabulary within DS has demonstrated that children present difficulties producing complex vocabulary categories, therefore two tiers of vocabulary were created: ‘basic’ vocabulary (nouns and verbs) and ‘complex’ vocabulary (adjectives and adverbs), to assess the effect of prompted reading on a large selection of vocabulary categories, rather than focusing on one particular type of vocabulary. These specific vocabulary categories are also applicable to the age range of children used in the study. Affirmatives (‘yes’, ‘no’ and ‘don’t know’) were coded for to investigate whether prompted reading affected the use of simplistic answers, specifically whether prompted reading decreased affirmative answers. Questions asked by children, like ‘what?’ and ‘why?’ were also included in the affirmative category, as they reflect an aspect of speech where a child is requesting for more information to further engage with the parent. Child questioning was rare and therefore did not require a category of its own. ‘Fillers’, additional words that make up a sentence, were also totalled. This was to investigate whether prompted reading facilitated more structured sentences, and therefore increased the number of fillers children produced. This was of particular interest for the DS group, as children with DS present difficulties in sentence structure. The total amount of vocabulary produced (inc. affirmatives and fillers) would therefore be equal to the total number of words produced. Literal and Inferential Parental Questioning and Language Production Children’s ability to respond to literal and inferential questioning during shared reading sessions was coded for by adapting a four-level coding system previously used in studies investigating literal and inferential language in pre-school aged children (Van Kleek et al, 2003; Tompkins et al, 2013; Engevik et al, 2016). Previous coding schemes were designed to assess children’s literal and inferential speech across four linguistic domains, where the first two levels (Level 1 and Level 2) resemble children’s literal language, and the second two levels (Level 3 and Level 4) represent children’s inferential language (Blank, Rose & Berlin, 1978). For the present study, children’s linguistic responses to literal and inferential questioning was only assessed under a 2 level system, where Level 1 represented speech in response to literal questioning, and Level 2 represented speech in response to inferential questioning. This adaptation was done to take into account DS children’s linguistic abilities, as a four-level coding system would have been too advanced for the particular task. Since DS children’s understanding of cognitive concepts and inferential questioning is limited, their linguistic responses to such questions would also be limited, therefore a two-level coding system was more acceptable. For each set of 12 prompted questions used, 50% represented literal concepts (Level 1) and 50% represented inferential concepts (Level 2). Level 1 coded for children’s responses to labelling prompts (“What is that?”- pointing at Bear) and vocabulary prompts (“What does ‘hollow’ mean?”). Level 2 coded for children’s responses to inference prompts (“Why did Bear fall asleep?”) and general knowledge prompts (“What else could Bear have used to stick the spoon to the arrow?”). Parental prompts where also coded and separated between literal and inferential levels. The number of textual prompts and parental prompts where coded using a binary counting strategy, as well as the level of each question (literal or inferential) recorded. For each prompt, children’s responses where coded based their correct or incorrect response and vocabulary production (nouns, verbs, adjectives, adverbs and affirmatives) so each child had a score of response and vocabulary production for literal and inferential questioning, between prompted and unprompted reading conditions. (An example of the coding system can be seen in Appendix A).This particular coding method was designed to assess the extent to which textual and parental literal and inferential prompts enhanced children’s linguistic qualities, and pin point whether a specific type of questioning facilitated more correct responses and production of more vocabulary. Scaffolding Techniques and Language Production Parents ability to successfully utilise scaffolding techniques between reading conditions was assessed, through designing a coding system that recorded each time parents took a break from reading the text to direct questions, these were labelled as ‘turn-taking sections’. The total number of turn-taking sections was coded, as well as the total number of questions parents asked per section and whether each question was literal or inferential. This was done to assess whether prompted reading encouraged parents to take more breaks from reading the text to ask their child questions, whether each time parents took breaks they asked more literal or inferential questions to engage their child. In addition to this, whether parental scaffolding enhanced children’s linguistic abilities were also assessed. This was done by coding the total number of words children produced per section, which would show whether parental scaffolding techniques enhanced children linguistic contribution. (An example of the coding system can be seen in Appendix B). Accuracy The accuracy of children’s responses, in relation to literal and inferential questioning, was coded by using a three-level coding system, used by previous studies investigating accuracy of children language during shared reading (Engevik et al, 2016). Previously, children’s accuracy of response was coded for along a linguistic continuum, where ‘fully adequate’ represented accurate verbal responses, ‘partially adequate’ reflected verbal communication which is ‘on the right track’ but not necessarily accurate, and ‘inadequate’ which represented any response that was irrelevant (Sorsby & Martlew, 1991; Engevik et al, 2016). Previous studies investigating accuracy of speech in DS children have adapted the coding system to merge ‘fully’ and ‘partially’ accurate categories together, to take into account the linguistic and cognitive difficulties DS children face (based on Engevik et al, 2016). However, the present study uses a slightly adapted version of the original coding system, where children’s ‘fully’, ‘partially’ and ‘not’ accuracy of responses were coded, yet only children’s ‘fully’ accurate responses will be used in the final analysis. This was done so children’s fully accurate responses to literal and inferential parental questioning could be assessed. ‘Partially’ and ‘not’ accurate responses were not assessed in this particular study as the sole interest is children’s ‘fully’ accurate response. The reason as to why ‘fully’ and ‘partially’ categories weren’t merged for the present study was to gain a more realistic understanding of children’s fully accurate responses, and merging categories would not provide this. (An example of the coding system can be seen in Appendix C).
Testing the Heat Hypothesis: The Relationship between Temperature and Violent Crime Rates
This paper explored the relationship between temperature and behaviour. In particular the effect heat has on violent crimes. The heat hypothesis states that increased ambient temperatures can cause increased aggressive motives and behaviours. The current study was longitudinal and archival. Data was collated from four different countries: U.S., Japan, Jamaica and Finland over a period of 40 years. Data was collected from reliable online sources for: Temperature in degrees Celsius (℃), rainfall in millimetres (mm), intentional homicide rates, assault rates, rape rates and burglary rates. Rainfall and burglary were control variables. Analyses revealed a significant and positive relationship between temperature and intentional homicide, assault and rape rates. Temperature and burglary were not significantly related. Such results provide support for the heat hypothesis. The relationship between heat and violent crime should be investigated further; as the effects of global warming increase, so may violent crime rates worldwide.
Data In accord with Anderson et al’s., (1997) methods, data of the following crimes were collected: intentional homicide, assault, rape and burglary within a specified 40 years. This crime data was sampled from the following countries databases: U.S., Japan, Jamaica and Finland. The inclusion criteria were to include the countries which had the most available data on crime. There were no data exclusions as the current study was retrospective, meaning all data had already been collected. The 40 years analysed within each country differed depending on data availability. Crime rates were collected in the U.S. between the years 1960 and 2000. Crime rates were collected in Japan between the years 1975 and 2015. Crime rates were collected in Jamaica between the years 1970 and 2010. Crime rates were collected in Finland between the years 1976 and 2016. Therefore there would have been 160 full observations of intentional homicide, assault, rape and robbery. However, due to limited data available there were gaps in the data. For the U.S., 40 full observations of intentional homicide, assault, rape and robbery were obtained. For Japan, 23 full observations were obtained and 17 partial. For Jamaica, 11 full observations were obtained and 29 partial. For Finland, 22 full observations were obtained and 18 partial. The crime data was police reported and per 100,000 of the population, as smaller figures were easier to manage. Crime data was collected from the following reliable online resources: Bourne et al., (2015), Burns (2013), (Knoema, 2011), (Nation Master, 2003), (Statista, n.d.), (Uniform Crime Reporting, 1930), (United Nations World Surveys, 2006), (UNODC Statistics, 1997). Websites were considered reliable if they were established official government data repositories. Temperature (℃) and rainfall (mm) data were also collected. This data was obtained from an online climate data portal (Climate Change Knowledge Portal, n.d.). Rainfall was included as a control variable to ensure that any significant effect was a consequence of increased temperatures, rather than reduced rainfall as a consequence of increased temperatures. If rainfall was not controlled for, it would be impossible to decipher whether the observed effect was caused by increased temperature or reduced rainfall. Apparatus Microsoft excel and the Statistical Package for the Social Sciences (SPSS) were used for data analyses. Analytical approach This study was a longitudinal archival study which analysed existing data. The dependent variable (DV) was crime rates per 100,000 people, collated from reliable online data sources. The independent variables (IV) were: temperature and rainfall. The question asked was whether crime rates can be predicted by temperature and rainfall. The control variables were burglary and rainfall. Burglary was a control dependent variable, as it was expected that temperature would affect violent crime and not non-violent crime such as burglary. Rainfall was a control independent variable, so that rainfall could be controlled for and this made it possible to detect whether temperature alone had an effect on crimes. The data collected required certain properties: the source had to be reliable, crimes had to be police reported and crime rates needed to be reported per 100,000 of the population. Pre-existing data available online was collected and sorted into an excel spreadsheet. Each variable had a column on the spreadsheet: country, year, intentional homicide, assault, rape, burglary, temperature and rainfall. The country variable was categorical. Countries were coded: 1 for the U.S., 2 for Japan, 3 for Jamaica and 4 for Finland. The remaining variables were continuous. There were 160 observations, 40 years per country. Some observations included data on all four crimes; some were partially completed due to limited data. Firstly scatter graphs were plotted with crime against temperature for each country. This revealed the general direction of the relationships between the temperature and crimes. The main analysis was a linear mixed-effects model, where temperature and rainfall were fixed effects and country and year were random effects. This analysis was chosen because of the structure of data. For this study there were multiple samples of crime rate data over 40 different years for each country, and multiple samples of crime rate data for the four different countries for each year. Magezi (2015) described how linear mixed-effects models can include such multiple, nested groups and accommodates for missing data. This was useful because the current study was a longitudinal archival study and consequently had missing data. Analyses were conducted using SPSS. An alpha level of .05 was used for each linear mixed-effects model. +1 lag model analyses for each crime were also implemented, to account for a possible delay of the effect caused by exposure to temperature. To achieve this, the DV columns were shifted down one row using SPSS. It was necessary to check that all values still aligned with the correct country.
Film language affecting behaviour: A psycholinguistic approach
Films are a popular form of art and entertainment that enable people to enjoy a story through multiple stimuli perception and stimulation of emotions. Plenty are the film elements that impact the audience’s attitude towards the film, yet language style has rarely been taken in consideration for research. This study focused on examining whether there exists a relationship between the audience’s favouritism for films and the linguistic style present in them, predominantly concentrating on emotional factors of language in films. A dataset containing the widest public ratings of films was obtained from the Internet Movie Database platform and paired with respective transcribed film dialogues provided by OpenSubtitles.org. The corpora’s transcripts (n=88,573) were analysed using the Linguistic Inquiry and Word Count software and all the variables produced were then correlated with IMDb’s weighted film ratings. The project found that all types of emotions present in transcripts of film language were significantly, negatively associated with the IMDb rating outcomes, while the effect sizes were small. This finding suggests there might be an inclination for emotions to be felt in other areas of stimuli perception, rather than verbal language, when it comes to films. Additional exploratory analyses showed how other variables correlated with film rating scores and practical application of study findings within the advertising industry were identified.
Dataset The dataset used for the study is purely secondary and consists of transcribed film dialogues (N=88,573) complemented with each film’s respective Internet Movie Database (IMDb) rating, which at the time of collection had a minimum of 100 user ratings per film. IMDb is an online film rating platform where the wider audience must register for an account and is then able to rate and review the films they have watched. Registered IMDb members rate films on a 10-point scale, with 1 indicating “terrible” and 10 indicating “excellent” (Boyd et al., 2020). IMDb’s rating algorithms produce ratings that are weighted by metrics associated with users, rather than average ratings. Although the algorithms are unavailable to the public, IMDb’s rating system has shown consistency across all films because the weighted ratings constantly provide reliability by reducing the possibilities of a small group of users to take advantage of the rating system (IMDb, 2021). IMDb is one of the most popular and authoritative film rating websites, where the total ratings of a film are anonymous and voluntarily provided (Sawers, 2015). The transcribed film dialogues data was provided by OpenSubtitles.org and the corpora was previously organised and used in a study by Boyd et al. (2020); it was generally provided by the authors for the purpose of this project. OpenSubtitles.org is an online website that provides transcribed and translated captions of motion pictures, audio files and various other audio-visual files (OpenSubtitles.org, 2021). The corpora used by Boyd et al. (2020) contains purely English-language film subtitles, corresponding to films originally released in English, or foreign films whose dialogues have been translated to English. Boyd et al. (2020) combined the transcribed film dialogues provided by OpenSubtitles.org with the IMDb ratings, along with other IMDb categories such as film genre, year of release, country of production, et cetera. Almost 90% of the IMDb categories linked to the films’ ratings are irrelevant for the purpose of this project, thus solely the film ratings will be taken in consideration for analysis. Automated Textual Analysis Software (LIWC) To conduct the automated textual analysis, this research project will use the Linguistic Inquiry and Word Count (LIWC) tool; also called “Luke”. LIWC is a textual analysis program that measures the degree to which various dimensions of words are used in a text (Tausczik & Pennebaker, 2010). LIWC program has two central features – the processing component and the dictionaries. The processing feature takes a text file and analyses it word by word, comparing each word with the dictionary files, sorting the word out as, for example, verb or second person pronoun (Boyd, 2017). Once the program finishes running, it produces an output where all the LIWC categories used in the text are listed, as well as the rates and percentages that each category was used in the given text. The dictionaries are at the heart of the LIWC program and they identify the group of words that belong to each category (Pennebaker et al., 2015). When the program was being created, the authors aimed at developing measures to define emotions present in words, cognitive processes, signs of self-reflection, et cetera, and in order to assign a psychological component to words, human judges contributed in developing the categories LIWC possesses today (Boyd, 2017). Across approximately 80 dimensions (see Appendix A), LIWC analyses the text in relation to various parts of speech, thinking styles, social concerns and emotions (Pennebaker et al., 2001). For example, the “positive emotion” category contains words such as “love”, “happy” and “nice”, while the “cognitive processes” category comprises words like “examine”, “think” and “understand”. Over the years, LIWC has been able to uncover psychological patters and personalities purely from textual analysis; Petrie et al. (2008) used LIWC to investigate the Beatles’ lyrics and found out that it was possible to distinguish each songwriter’s unique language style, and also to discover whose Beatle’s style was predominant in collaboratively written songs. Researches have shown LIWC to be one of the most reliable automated textual analysis tools that is able to uncover and predict psychological implications residing in written sources, thus this study will employ this tool to test its hypothesis. Data Preparation and Analysis The initial corpora was subjected to cleaning procedures, where data which did not meet all inclusion criteria was removed from the dataset. The inclusion criteria consisted of film ratings having at least 100 user votes, transcribed dialogues having at least 100 words and corpora variables containing all data values. The cleared dataset (N=85,130) is going to be tested in the LIWC program, where each word within the transcripts will be counted and sorted among the LIWC dictionary categories it belongs to. For the main hypothesis, the program will analyse the dataset for LIWC variables that have been shown to be correlated with positive and negative evaluations in the past. This way, the quantified rates of positive and negative emotion words in each dialogue will be identified. Once the rates have been extracted, a bivariate Pearson’s correlation will be conducted to assess whether there exists a significant relationship between positive and negative emotion words in film dialogues and their IMDb ratings. Additionally, exploratory analyses will be run to search for significant relationships between the dataset variables and the film ratings, again by conducting Pearson’s correlation tests between the ratings and all LIWC variables produced.
A Scoping Review of the Effects of Benzodiazepines on Emotions in Young People
Benzodiazpines, Young people, Children, Adolscents, Emotion/s, Emotional dsyregualtion, Non-prescription misuse.
Background: Benzodiazepines are primarily used to manage anxiety and agitation. While it is understood how benzodiazepines work physiologically it is not fully understood how these physiological changes cause the emotional changes. As this relationship is not fully understood, it maybe that benzodiazepines also affect emotions in ways not currently known, such as being a factor in emotional dysregulation. Objective: To conduct a scoping review into the effects of benzodiazepines on young people. To map the of the effects benzodiazepines have on emotions in young people and identify any links between benzodiazepines and emotional dysregulation. Design: A scoping review was conducted. PRISMA protocols were followed but other sources such as Cochrane and Joanna Briggs Institute were consulted to develop a framework. Results: This review’s findings suggests that benzodiazepines do reduce anxiety and agitation. However, the research concerning children and adolescents is limited, and suggests benzodiazepines maybe less effective than in adults. There are many adverse effects but despite this prescription use remains relatively high. Non-prescription misuse in adolescents is evident and globally prevalent. Only one direct link was found to emotional dysregulation, but other possible links were also found. Conclusions: More research into the areas of the efficacy of benzodiazepines in children and adolescents and the risks associated with paradoxical and adverse effects is needed. Possible links between emotional dysregulation and benzodiazepines misuse were made and research is needed to understand if this relationship exists and the effects. Any improvement in understanding this relationship will enable targeted interventions to be developed.
The search was conducted using the following databases: Web of Science, PubMed, CINAHL, Psych Info, Medline and Embase. Searches were dependent on the functionality of the different databases such as different key terms, different abilities to expand search terms and different limiters or age groups, these are all shown in the search terms document in the OSF repository. All searches were limited to English language. No further sources were used to supplement the search.
A secondary data analysis: How will the effects on accuracy differ when measuring individual differences in word reading skill in Spanish?
Individual differences, Dyslexia, Word property effects, Language orthographies, Reading accuracy
A deficit in accuracy has been found to correlate to reading difficulties (Davies et al., 2007). Effects of psycholinguistic factors and differences in language orthographies contribute to reading skills, predominantly in children with reading impairments such as dyslexia. The present study is a secondary data analysis of the original research conducted by Davies et al. (2007). The effects on accuracy of individual differences demonstrated by nonword reading skill and word property measures were examined in Spanish children. Participants were 110 students differing in reading ability from schools located in A Coruńa, Lugo, Orense and Pontevendra in northern Spain. The subjects were required to take standardized and experimental reading ability and intelligence tests. Eight lists consisting of 15 words each were created. The words were presented in five rows of three columns. Participants were asked to read the words as quickly and accurately as they could. Words which were incorrectly pronounced were identified as errors. Word property measures suggested to affect reading ability were selected and updated from an online database of Spanish words ‘EsPal’. Variables of frequency, length of words, neighbourhood size (Levenshtein distance), RAN, PROLEC-R nonword reading were investigated in the present analysis. Accuracy of reading scores was found to be significantly high for the sample. Effects of individual differences on accuracy were noted. Word property measures of frequency and neighborhood size were found to significantly affect reading accuracy. Effects of fluency (RAN) and nonword reading (PROLEC-R) were also observed. The analysis provides insight into plausible factors which contribute to reading impairments in a rule governed orthography such as Spanish. Results suggest that perhaps nonword reading skill could serve as an marker for reading difficulties.
Participants In the original study (Davies et al.,2007) researchers selected and identified three groups of children from an initial sample of 110. Children who indicated clear reading disabilities (DYS/ dyslexia), a control group consisting of children matched by reading ability level (RA matched group) to the DYS group and a chronological age control group (CA matched group). The present analysis investigated the whole sample of 110 participants and no group selection was conducted. Participants were students from schools located in A Coruńa, Lugo, Orense and Pontevendra in northern Spain. 110 children differing in reading ability and age were selected. These children did not obtain any prior diagnoses of impaired neurological or sensory-motor functioning. The sample of 110 children was required to take standardized and experimental reading ability and intelligence tests on different school days during a 3-month time. Experimental data was gathered in a single session focusing primarily on the experimental test, whereas the standardized reading test was given in a separate session. Measures Reading performance was measured across a series of ability tests (PROLEC-R, RAN). PROLEC-R Battery Tests of Literacy Skills Evaluation of reading processes for children is assessed through the use of the PROLEC-R battery constructed by Cuetos, Rodriguez, Ruano & Arribas (1996). The battery consists of Spanish tests analyzing reading processes such as lexical, semantic etc. Subjects were required to read from a list of 40 words as quickly and accurately as possible. Words differed on properties such as frequency and length. The scores obtained consist of a score relating to accuracy and reading speed when assessing words and nonwords. It has been suggested that the results of the test provide significantly more information when combining the PROLEC-R scores of accuracy and PROLEC-R reading times. This is why PROLEC-R nonword reading was computed into a combined measure. This was done by dividing accuracy by time. Rapid Automatized Naming Tests (RAN) Rapid automatized naming (RAN) refers to how quickly a child can read aloud a set of previously known items. These items can include numbers, pictures, letters, colors etc. A child’s performance on the tests is assessed by comparing their reading times to the norm scores of children in the same age. RAN tests are designed to predominantly assess fluency of reading. It is suggested that RAN influences reading scores as it requires the retrieval of stored phonological information (Johnson & Eden, 2014). Children were presented with a sequence of rows consisting of sets with different items (colors, letters, pictures etc.). The subjects were required to read aloud all the items from the list starting from top to bottom. Accuracy of reading and time it took for the child to name the words were recorded. Children with reading difficulties will be expected to present a delay in reading speed and accuracy, thus scoring low on the RAN tests. Word Property Measures In the original study (Davies et al.,2007), words were chosen varying on lexical frequency (high or low frequency word), orthographic neighbourhood size (many or few neighboring words) as well as word length (short or long in length) (factorial design 2x2x2). Updated word property measures were derived from the EsPal (“Español Palabras” meaning “Spanish words”) repository consisting of properties for Spanish words. The new word property measures derived from the database (frequency, length of words and neighbourhood size) were compiled together with the old data. The system is able to process different corpora in the same way. It combines a corpus which is derived from movie subtitles and one from previously written text such as Web pages, fiction, nonfiction writing etc. The updated measure of frequency is reported within the analysis with the databases original name “esp.count”. The ‘count’ refers to the number of times in which the word appears within the selected corpus. For orthographic neighbourhood size, all words are counted within EsPal and are in turn compared to other words within the corpus. Yarkoni et al (2008) argued that the orthographic neighbourhood metric (ON) developed by Coltheart et al.(1977) is limited due to the nature of its definition. ON is the number of words which can be developed by substituting one letter in the other word given that it is the same length. As a result, researchers have developed a new measure of orthographic neighbourhood size which is less restricted than the previous metric. The new measure is coded as Levenshtein distance 20 (Lev_N) (Duchon et al.,2013). Levenshtein distance refers to the average distance of 20 words which are found closest in text. LD is calculated as the number of edits to words (substitutions, insertions, deletions) which are needed to change one word into another. For example, the Levenshtein distance between the word “SMILE” to “SIMILES” is two, as it differs from the original by adding the letters “I” and “S” (Yarkoni et al., 2008). An updated measure of length of words was also derived from the EsPal database and is coded as “esp.num_letters”. This refers to the word length which is expressed in number of letters. Procedure Eight lists consisting of 15 words each were created. Participants were shown each list of words on a A4 sheet of paper. The words were presented in five rows of three columns. Participants were tested individually and were asked to read the words as quickly and accurately as they could. Words which were incorrectly pronounced were identified as errors. Three types of errors were identified: word substitution, nonword and stress errors. An example of word substitutions would be the word “nube” (cloud) which would turn into "neuve “(nine). For nonwords: “bigote” (mustache) would be “bixote”. For errors relating to stress “cáfe” would be “café”. All responses from 110 participants were computed and are present in the file: “SpanishR”. Accuracy is presented as the subject responses scored as correct and incorrect (0,1). Analysis Item level and subject level data about word properties and subject attributes were extracted. An analysis of the accuracy of responses as well as the effects of word properties on reading was conducted. Errors were scored as 0,1; correct and incorrect. Random and experimental variables were identified. Random effects were specified as “palabra” (words) and “subject identifier” (participant name). The experimental/fixed effects were specified as frequency, length, neighbourhood size, RAN, PROLEC-R nonword reading. To investigate correlations between the experimental variables a correlation matrix was constructed. Generalized linear mixed effects modeling (GLMM; Baayen, 2007) was used in order to analyze the accuracy of responses made by children to reading words. The distribution of variables included in the model relate to person characteristics and word characteristics. Moreover, GLMM was used to capture the randomness of the sample to increase accuracy of estimates for the effects of individual differences on word properties. The model explains the variation of accuracy by incorporating experimental and random variables. Model development followed a stepwise process, adding one variable to each model at a time. The primary model specification was as follows: accuracy~(1|palabra) + (1|subj_identifier), data = spanishr. A table of estimates of both random and fixed effects were created and analyzed in order to assess the variation in the models.
Data set belongs to Robert Davies who is the author of the original published study (Davies et al.,2007, “Reading development and dyslexia in a transparent orthography: a survey of Spanish children”.)
The present work is a secondary data analysis of the original research conducted by Davies et al. (2007), “Reading development and dyslexia in a transparent orthography: a survey of Spanish children”.
English and Spanish (Spanish participants, words, database)
The Effects of Different Sleep Stages on Language Learning Tasks in Young Adults
Language learning, novel generalisation, REM, sleep, sleep spindle density, sleep stages, speech segmentation, SWS
In order to learn a language, one must practice multiple tasks, including speech segmentation and generalisation. Segmenting speech allows for the identification of words and learning the meaning as well as syntactic role of those words within phrases and sentences. Novel generalisation requires generalising over the structure of a new language not yet experienced. Frost and Monaghan (2016) showed that participants were able to use the same statistical information at the same time to complete both language tasks. They suggest that segmentation and grammatical generalisation are dependent on similar statistical processing mechanisms. The role of sleep for learning to segment and generalise language is still unclear. Sleep affects memory consolidation, which is necessary for learning a novel language. This refers to the amount of sleep individuals get within their sleep cycle, yet it is unknown whether the duration of separate sleep stages has an effect. The declarative/procedural (DP) model by Ullman (2004) on learning provides distinctions in DP memory that associate with slow-wave sleep (SWS) and rapid-eye movement (REM) sleep respectively. SWS has a role in declarative memory processes, including memory for words and grammar. Rapid-eye movement (REM) sleep has a role in procedural memory processes, involving motor skills and coordination. Sleep spindle density should also be considered, as spindles are involved in offline information processing and information transfer. It was found that increased SWS and stage 2 spindle density have a positive effect on speech segmentation compared to generalisation.
Participants The original experiment was completed by 54 participants, 8 males and 46 females, with an age range of 18-24-years-old (mean age = 18.52). All participants reported being native-English speakers, with no history of auditory, speech or language disorders known. All participants either received university course credit or £20 for completing the experiment. Observations may be excluded for the first linear mixed-effects model. Exclusions may come from participants in the sleep group who did not sleep during the permitted time. This is because the first analysis aims to compare sleep vs. wake. The same participants’ data will be kept for the other linear mixed-effects models which aims to compare duration of sleep stages. This research received ethical approval by Dr Padraic Monaghan and Lancaster University’s Psychology Department on 22/04/2021. Design This study had a between-participants design with two conditions: sleep vs. wake between training and testing, and test type. There were two test types of speech segmentation and novel generalisation. Participants were randomly allocated to the sleep or wake conditions, and split evenly, meaning 27 participants slept and 27 remained awake. This study had access to PSG data for 18 of the participants in the sleep group. All participants received both test types. All participants were provided with an information sheet and gave written consent before the study commenced. Materials Stimuli Using the Festival speech synthesiser (Taylor et al., 1998), speech stimuli were created that were based on similar stimuli used by Peña et al. (2002). This artificial training language contained monosyllabic items, of which there were nine (pu, ki, be, du, ta, ga, li, ra, fo), used to form three different non-adjacent pairings with three possible X items in-between (A1X1–3C1, A2X1–3C2, and A3X1–3C3) (Frost & Monaghan, 2016). Using Peña et al.’s (2002) study, A and C items contained plosive phonemes (pu, ki, be, du, ta, go) and X items contained continuants (li, ra, fo). All AXC item strings had a duration of approximately 700ms. Any preferences – for dependencies not due to the statistical structure of the sequences – were controlled for by generating eight versions of the language. Each version had randomly assigned syllables to A and C items, and the same X items were used in all versions. These versions of the language were counterbalanced across both task types. When testing for novel generalisation, three additional syllables were used with continuant phonemes (ve, zo, thi) (Frost & Monaghan, 2016). Research on the similarities in phonological properties of non-adjacent dependent syllables has shown that these similarities show support for acquisition of such nonadjacencies (Newport & Aslin, 2004). Nonetheless, other research has found that they are not essential for language learning to occur (Onnis et al., 2004). Words in the same grammatical category tend to be coherent regarding phonological properties (Monaghan et al., 2007), so regardless of learning, this property of the artificial language used within this study is consistent with natural language, which allows for real-life implications. Training The speech stimuli were formed into a 10.5-minute-long continuous speech stream by stringing together the AXC words within the language. It was ensured that no Ai_Ci dependencies were repeated immediately after each other. The speech stream included 5s fades for the onset and offset of speech, which ensured that such a feature of speech could not be used as a language structure cue (Frost & Monaghan, 2016). Testing Segmentation: part-words were trisyllabic items that were heard in the training speech stream but overlapped word boundaries. As such, part-words comprised of either the last syllable of one word and the first two syllables of the next (CiAjX), or the last two syllables of one word and the first syllable of the next (XCiAj). For all nine AXC items, both part-word types were created. 18 test pairs were constructed which participants listened to, by matching each part-word with its corresponding word (for example, the A1X2C1 item was paired with the X2C1A2 part-word) (Frost & Monaghan, 2016). Novel generalisation: nine forced choice tests included a rule-word which contained one of three novel syllables (ve, zo, thi) (AiNCi), where N is the novel syllable and a novel part-word. For each Ai_Ci dependency, each novel rule-word appeared once. Part-words were made of two syllables that were heard in the training task, in their respective positions, with the same novel syllable as in the rule-word sequence (Frost & Monaghan, 2016). This novel syllable could appear in any position (first NCiAj, second XNAi, or third CiAjN) and each novel syllable occurred once in each of these positions. Rule-word and part-word novelty presence controlled for the effect of the novel syllable, yet the novel generalisation task still tested for generalisation of the non-adjacent structure of items within speech (Frost & Monaghan, 2016). Randomisation of test-pairs in all conditions was ensured across all participants, including the position of the correct response in each test-pair, to reduce response bias. When listening to the test-pairs, items in each pair were separated by a 1s pause. All participants completed The Stanford Sleepiness Scale (SSS) (Hoddes et al., 1972). This was in order to note participant sleepiness before the period of sleep or wake. The SSS consists of one item on a scale of seven statements, within which participants were required to select one statement that best described their perceived level of sleepiness (Shahid et al., 2011) (see Appendix A). Participant responses in the testing task were excluded if 90% of responses were always “1” or “2”, or if responses alternated between “1” and “2”. Procedure The whole procedure lasted for a three-hour period. For the training task, all participants listened to the continuous stream of speech and were instructed to pay attention to the language and think of possible words it contains. After the training task was complete, participants were split into two groups for the sleep vs. wake condition. Half of the participants, the sleep group, were given an hour and 45 minutes to sleep. These participants slept at Lancaster University Psychology Department’s sleep lab, and their sleep was monitored using polysomnography (PSG). PSG and an Embla N7000 system can record the amount of time spent in each sleep stage, and sleep spindle density, with EEG sites: O1, O2, C3, C4, F3, and F4 referenced against M1 and M2. The other half of participants remained awake for the same duration, watching a non-verbal, emotionally neutral video with neutral music. The testing task was then given to all participants after the same amount of time, 15 minutes after the break period. All participants were then required to complete the testing forced choice tasks. Within each trial, participants listened to a test-pair of items and were instructed to select which item best matched the training language. A response of “1” for the first item or “2” for the second item on a computer keyboard was recorded. All participants listened to the speech using closed-cup headphones in a quiet room (Frost & Monaghan, 2016). To test speech segmentation, participants completed a forced choice task on preference for word/part-word comparisons. To test novel generalisation, participants completed a similar forced choice task for rule-word/part-word preference. Data analysis Analysis included mixed-effects models to allow for random participant and item variability. As all participants responded to both task types, therefore multiple items, the likelihood of correlations in responses from the same participant and to the same item increases. Generalised linear mixed-effects allow for a more flexible approach compared to ANOVA, that can handle missing data better, without significantly losing statistical power. Participant and item variation, the effects of sleep/wake, test type, and sleep stage duration were all considered. The interactions between sleep/wake and test type, and sleep stage duration and test type, were also considered in separate models.
Secondary data analysis. Data were originally collected for the paper below, but they were not analysed by the authors. Frost, R. L. A., & Monaghan, P. (2016). Simultaneous segmentation and generalisation of non-adjacent dependencies from continuous speech. Cognition, 147, 70- 74
Data/Excel.csv Data/Excel.xlsx Analysis/r_file.R
Third Parties and Police Use of Lethal Force: Evidence from the Mapping Police Violence Database
Lethal force, Third Parties, Police Citizen Interactions, Use of Force
Over recent years media coverage has highlighted the use of excessive force by some police officers. The use of lethal force towards black and other ethnic minority citizens has been identified as a cause for significant concern. Research in the bystander literature and in non-fatal force policing contexts has identified that third parties can have positive impacts in reducing the severity of these incidences. The role of third parties in fatal force events, however, has not been investigated. This is something which the current study seeks to address. The Mapping Police Violence database was used to identify a year’s worth of lethal force events in the US. Newspaper articles relating to these incidents have been coded in line with a predefined coding framework to examine the presence of third parties in these incidents, and the nature of any social relationships with third parties in relation to the type of lethal force utilised. The results revealed that third parties were present in just under half of incidences and that the presence of a third-party with a pre-existing social relationship to the citizen was associated with a lower likelihood of officers utilising forms of ‘less lethal’ force to the extent that it results in a citizen fatality. These findings highlight the potential importance of third parties in understanding the nature of lethal police citizen interactions, and also the potential protective role the presence of known others may have in reducing the likelihood of officers excessively utilising forms of less lethal force.
A secondary data analysis was utilised to examine the presence of third parties in incidences of police use of lethal force. The Mapping Police Violence database (Mapping Police Violence, 2020) was the primary dataset utilised for the study. This is a freely available and open public database compiled by researchers in the US which aims to provide a record of all police involved deaths in the US. This database has been recording police involved deaths in the US since 2013, primarily gathering information through news articles published by various American news outlets. The type of force engaged in by officers that resulted in death was utilised as the outcome variable. The predictor variables were the presence of third parties, the presence of any known third parties, or unknown third parties, the number of officers present, the presence of other emergency services, the location of the incident, the race of the citizen, the gender of the citizen, the alleged presence of a weapon, the initial reason for the encounter, the presence of any digital technology capturing the event and the level of threat posed to the officer. The Mapping Police Violence database records multiple variables in relation to these incidences, including individual and situational factors. Several of the predictor variables included in the current study have been gathered from this dataset; specifically, the type of lethal force used, the alleged presence of a weapon, the race of the citizen, the gender of the citizen, the level of threat posed to the officer, the initial encounter reason and the presence of a body worn camera. Within the current study, most of these variables have been used as recorded in the dataset, however, the level of threat posed to the officer has been recategorized. The multiple different levels of threat recorded in the dataset have been regrouped into three categories: attack (indicating the greatest level of threat to the officer), other (referring to any other level of threat), and none (for incidences in which it was clear there was no threat to the officer). In the original data only the presence of a body worn camera is recorded. For the current study this variable has been transformed to include the presence of any digital technology capturing the event, such as CCTV or smartphones, as research has found that the presence of any digital technology and not only a body camera can affect police citizen interactions (Shane et al., 2017). The Mapping Police Violence database records the citizen’s cause of death in relation to the type of force utilised. In incidences where multiple types of force have been identified as contributing to the citizen’s death, the database records a list of all types of force involved. The types of force included in the database include gun, taser, pepper spray, baton and physical restraint. For the current study, these types of force have been grouped, to provide an outcome variable with fewer levels. The grouping of the outcome variable has been done in line with previous research looking at police use of force, which identified a gun as a distinct type of force due to the increased risk of lethal outcomes. The other types of force are grouped into a second category of other types of ‘less lethal’ force, as these types of force have been identified as alternatives to the use of a gun, which would be expected to reduce the likelihood of a citizen fatality (Sheppard & Welsh, 2022). In incidences where multiple types of force were used, the most severe form of force has been recorded; for example, if the cause of death is attributed to a gun and a taser, then this incident would be recorded as a gun as the type of lethal force utilised. The dataset contains links to the news articles which have been used to gather information regarding each of the individual police involved death incidences. The variables included in the current study relating to the presence of others were gathered by coding these news articles which are linked in the database to the individual incidences of police involved deaths between 6th March 2022 – 6th March 2023, providing a sample of 1,257 police involved deaths. News articles are a source of information which have been identified as having certain limitations, particularly relating to potential media bias in the reporting of crime related stories (Lawrence, 2000). Research looking at the reporting of police use of force incidences by newspapers, however, has found that for many factors there was consistency between news reports and police reports of the same incidents (Ready et al., 2008). For the current study, news articles are utilised due to the promise they provide in allowing the events of police involved deaths to be examined in relation to the presence of third parties. To identify the relevant incidences for the current study, three primary exclusion criteria were applied prior to the coding of the news articles. Firstly, to identify incidences with news articles with sufficient information to allow the presence of third parties to be examined, a minimum word count of 150 words was required in at least one of the associated news articles. Secondly, as the study’s primary interest was in the use of lethal force, which involves an on-duty officer using force, only incidences relating to on duty officers were included. Finally, incidences in which the use of force by the officer was accidental, such as car crashes that police officers were involved in, were excluded, as these events have different characteristics to those in which officers intentionally engage in the use of force towards a citizen. The application of these exclusion criteria left a sample of 1052 incidences of police use of lethal force. To investigate the presence of others in these incidences, prior to the analysis a predefined behavioural coding scheme (Philpot et al., 2019) was created and applied to the news articles to capture the presence of third parties. This coding scheme contained 12 individual items capturing the presence of third parties and any social ties between third parties and the citizen involved in the incident (See Appendix A for the full coding scheme). Two additional items were included to capture the presence of multiple officers or other emergency services. One code regarding the location of the incident was also included to capture whether it occurred in a public, semi-public or private location. Each of the items were coded for presence with a 1, their absence recorded with a 0, or if it was not clear whether this item was present a 99 was recorded. In total 15 codes were included in this behavioural coding scheme. Here are some examples of these codes relating to the presence of third parties: “The presence of a third-party with a pre-existing social connection to the primary citizen involved” “The presence of more than one officer” “The presence of a third-party with no pre-existing social connection to the primary citizen involved” To facilitate the process of coding the news articles in line with the coding scheme, a Qualtrics survey (https://www.qualtrics.com) was created. This survey presented the individual items within the coding framework in a questionnaire format, allowing the items to be coded in the format of closed ended responses to questions relating to the presence of third parties. The responses from the survey were then transferred to an Excel document to allow the data to be prepared for analysis. Ethical approval has been obtained for this study. The study has been reviewed and approved by a member of the Lancaster University Psychology Department, the ethics partner of the supervisors. The reliability of the coding scheme and its application to the news articles was assessed through the double coding of 10% of the sample by a second researcher separately to the primary researcher. To assess the level of agreement between the two researchers for each variable, Gwet’s AC1 (Gwets, 2014) coefficient was calculated. In line with the recommendations of Landis and Koch (1977), the resulting coefficients were interpreted in the following way: a value of 0.4 or above indicating moderate agreement, a value of 0.6 or above indicating substantial agreement, and finally a value of 0.8 or above, indicating almost perfect agreement between raters’ scores. For 13 of the variables an agreement level of substantial or almost perfect was reached, as seen in table 1 (appendix B). For the variable relating to the third-party being a friend of the citizen there was no variation in responses (i.e., 100% agreement), and therefore a coefficient could not be calculated. For the location variable, only a moderate level of agreement was found, as a result this variable was excluded for the purpose of analysis. Figure 1 depicts a flowchart of the process undertaken to sample the relevant incidences. The first part of the flowchart shows the initial process that was undertaken to identify all police involved deaths recorded in the Mapping Police Violence database in the prior 12 months. Following the initial data collection procedure descriptive statistics were run which highlighted that in the initial sample of 1052 incidences there was very limited variation in the outcome variable of the type of lethal force utilised by officers, with 990 incidences involving a gun as the primary cause of death, and only 62 incidences involving other forms of force. In this initial sample a citizen’s cause of death not involving a gun would statistically be considered a rare event, which would have presented challenges in utilising this variable as the outcome in any subsequent analyses. In line with the recommendations of research (Shaer et al., 2019), an oversampling approach was chosen to overcome the limitations of having a rare event in the outcome variable, with further incidences in the dataset that did not involve a gun as the cause of death being oversampled so at least 10% of the sample involved a cause of death other than a gun. As can be seen in figure 1, for these incidences to be as similar to the primary sample as possible, they were only sampled for the three preceding years to limit any additional sample variation that may have been introduced by sampling a wider date range. This led to the identification of a further 182 incidences where the citizen’s cause of death did not involve a gun. The same exclusion criteria were then applied to this sample, with a further 65 incidences excluded, leaving a sample of 117 additional incidences which were coded in line with the same procedure as the initial sample. This oversampling procedure led to a final sample of 1169 incidences. The data analysis involved chi square tests of independence, to examine whether the presence of others during fatal police citizen interactions had a statistically significant relationship with the outcome variable of the type of lethal force utilised by officers. Due to the exploratory nature of the study there was not a predicted direction or nature of the relationship between the predictor variables relating to third-party presence and the type of fatal force utilised by officers (McIntosh, 2017). Prior to the main analyses, descriptive statistics were run to investigate distributions within variables and to allow any rare event variables to be identified.