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Record W76894055

A Comparison of Canadian and American Offender Stereotypes

2013· article· en· W76894055 on OpenAlexaboutno aff
Meredith Allison, Laura Sweeney, Sandy Jung

Bibliographic record

VenueNorth American journal of psychology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyStereotype (UML)Social psychologyAffect (linguistics)Race (biology)White (mutation)PerceptionCriminologyGender studiesSociology
DOInot available

Abstract

fetched live from OpenAlex

When asked to think about the characteristics of criminal offenders, what comes to mind? A stereotype is an inflated belief associated with a particular used to justify (rationalize) our conduct in relation to that category (Allport, 1979, p. 191). Research on offender stereotypes has suggested that people do hold stereotypes of offenders (MacLin & MacLin, 2004) and that these stereotypes can affect one's perceptions of defendants (Yarmey, 1993). Thus, it is important to examine stereotypes because such beliefs can affect legal decision-making (Landy & Aronson, 1969). Some researchers have studied which demographic characteristics are associated with the general offender stereotype. For example, participants in Reed and Reed (1973) perceived the typical criminal as an uneducated male who had psychological issues. Madriz (1997) found that the typical criminal was male and Black and/or Hispanic. Some of her participants also described criminals as immigrants. MacLin and Herrera (2006) asked participants to list the first ten things that came to mind when they heard the word criminal. Here, the typical criminal was seen as male. In terms of race, Blacks had the highest ranking (40%), followed by Hispanic (30%), White (20%), and Asian (10%). MacLin and Herrera's (2006) study suggested that the typical criminal was seen as a male, a visible minority, and on average, 25 years old. When it comes to social categories, race has been a major focus in stereotype research. In one study, participants were asked to rank different and the likelihood that they are perpetrated by various racial groups (Gordon, Michels, & Nelson, 1996). The results showed that Blacks were seen as more likely than other racial groups to commit blue-collar crimes, such as aggravated assault, motor vehicle theft, and violent offenses. Whites, in contrast, were seen as more likely to commit white collar crimes such as embezzlement, forgery, and fraud. Similarly, Welch (2007) noted that in the United States, Blacks/African Americans are perceived as more likely to be offenders in general, perpetrators of violent in particular, and that these stereotypes contribute to racial profiling. There is some suggestion that such stereotypes of Blacks hold across cultures. Henry, Hastings, and Freer (1996) surveyed Canadian community members. They found that 37% of participants believed that there is a relationship between racial/ethnic group and the likelihood that a person would be involved in crime. Of the participants who linked race and crime, a majority (61%) believed that the groups most responsible for crime were Jamaicans, other West Indians, and Blacks. Stereotypes regarding gender and crime typically have focused on views of women as victims of crime (Howard, 1984). In terms of female offenders, there have been some studies on women as perpetrators of rape. Specifically, several studies have noted that females are not seen as typical perpetrators of rape, especially the rape of male victims (Smith, Pine, & Hawley, 1988; Struckman-Johnson & Struckman-Johnson, 1992). As a result of such gender stereotypes, female offenders are often treated more leniently than male offenders in cases involving rape (Davies, Pollard, & Archer, 2006; Smith et al., 1988) and robbery (Ahola, 2012). Researchers have focused less on the stereotype concerning the typical offender's age. In the psychology and law realm, what research exists on age and stereotypes has tended to focus on older adults and children as victims and witnesses rather than as offenders (Lachs et al., 2004; Mueller-Johnson & Ceci, 2007; Ross, Dunning, Toglia, & Ceci, 1990). One age group that has received some recent attention in the stereotype literature is that of juvenile offenders. Haergerich, Salerno, and Bottoms (2012) suggested that there may be two subcategories of the juvenile offender stereotype: Superpredator and Wayward Youth. …

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.074
GPT teacher head0.424
Teacher spread0.351 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2013
Admission routes1
Has abstractyes

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Same venueNorth American journal of psychologySame topicCrime Patterns and InterventionsFrench-language works237,207