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Record W2104805308 · doi:10.3138/cjccj.45.3.391

Media Hype, Racial Profiling, and Good Science

2003· article· en· W2104805308 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsRacial profilingProfiling (computer programming)NewspaperPublicityInjusticeRacismPsychologySocial psychologySociologyLawMedia studiesPolitical scienceComputer scienceGender studies

Abstract

fetched live from OpenAlex

The requirements for good science are basically simple. They comprise a clear understanding of what is being investigated; objective and reliable collection and recording of observations, findings, or data; and rational analysis of those observations, findings, or data in order to draw sound conclusions. The requirements for articles that sell large numbers of newspapers are clearly different, comprising good stories or anecdotes, generally told by sympathetic victims of some injustice or other, accompanied by sweeping generalizations couched in emotional or provocative language. The latter masquerading as the former is what is found in the Toronto Star's articles claiming to have statistically proved racial profiling on the part of the Toronto Police Services. Anecdotal evidence of racial profiling and the fact that there is, in many quarters, a belief in racial profiling are significant and important social realities. But as evidence of the reality of some objective phenomenon to which that label is being attached, such anecdotal evidence is unacceptable. Anecdotal evidence speaks more to beliefs than facts, especially when the anecdotes and beliefs are themselves being widely publicized in the media. There is more than a real possibility of a vicious circle or self-fulfilling prophecy regarding racial profiling, which begins with claims, is fuelled by publicity, and leads to stronger belief and more claims. An even greater possibility of self-generating smoke without real fire exists where the beliefs have spawned a multimillion-, if not billion-dollar industry devoted to the problem. An Internet search on racial profiling returns tens of thousands of American Web pages. The American Civil Liberties Union has made attacking racial profiling one of its top contemporary concerns, filing several lawsuits, preparing numerous publications and presentations, and highlighting the issue in fundraising materials. Federal and state legislation has been passed in the United States regarding the matter. Several leading experts have built careers and produced best-selling books on the topic, as well as signing on as consultants or expert witnesses on the issue. Conferences have been devoted to the topic, and local and state and federal government departments have been created to deal with the issue. Without any recognition of historical or other differences between the United States and Canada, on the topic of racial profiling our longest undefended border is truly undefended; the American literature and experience has been simply imported in its entirety and assumed holus bolus to be applicable to Canada. The existence of numerous anecdotes and widely held beliefs about racial profiling is cause for concern because of the high social costs involved. It is a matter of great importance that a community believes it is being unfairly treated by the police, completely aside from the question of whether that belief is objectively true. How such a situation arose may be less significant than its resolution. Such a problem requires solutions focused on improving communications, building mutual trust, increasing transparency to allay fears, and ensuring proved occasions of impropriety are quickly and sternly dealt with. On the community side, it also requires an appreciation of the potential for self-serving claims that are either intentionally or even unwittingly false. Guilty accused, unsurprisingly, may use every conceivable avenue to escape punishment. The reality of false, self-serving claims of racial bigotry or harassment must be acknowledged by the relevant group. It is most unfair to the police to demand that every claim of professional impropriety be presumed valid. The necessity for demanding evidentiary verification of claims of bigotry or other impropriety must be appreciated by the relevant community, although, of course, the fairness and other aspects of the verification process can be assessed to ensure they meet appropriate standards. …

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.

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)0.005
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.141
GPT teacher head0.366
Teacher spread0.225 · 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