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Record W2589762565

A “Criminal Immigrant” Mindset and Punitiveness: The Canadian Case

2016· article· en· W2589762565 on OpenAlexaffabout
Steven D. Brown, Anthony Piscitelli

Bibliographic record

VenueInternational journal of criminology and sociological theory · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsMindsetPsychologyImmigrationSocial psychologyMediationIngroups and outgroupsEthnic groupOutgroupMulticulturalismCriminal justiceCriminologyPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

Unnever and Cullen (2010) argue that there is a “culturally universal” relationship between racial/ethnic/immigrant animus and general punitiveness.  Because this thesis seems ill-fitting to Canada’s multicultural society, we re-examine the connection in Canada between punitiveness and intolerance associated with new immigrants. We do this by expanding their multivariate analyses of the Canadian case to consider additional data sources spanning the first decade of this century, and by testing directly their thesis that the relationship is mediated by citizens imputing criminal activity to negatively-viewed outgroups.  We show that the relationship between immigrant intolerance and punitiveness reported in their original research for the year 2000 remains strong in 2004, 2008 and 2011 and resists explanation in terms of potentially relevant third variables. Our supplementary study examining the capacity of a criminal immigrant mindset variable to mediate this association shows that mediation is partial only. We conclude (1) that outgroup animus and general punitiveness are indeed related in the Canadian case, (2) that there is modest support for the Unnever/Cullen account of that relationship, but (3) that most of the original relationship remains unexplained.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.095
GPT teacher head0.371
Teacher spread0.276 · 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 designTheoretical or conceptual
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

Citations1
Published2016
Admission routes2
Has abstractyes

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