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Record W3114948580 · doi:10.1080/02722011.2020.1831139

Profiling the Future: The Long Struggle against Police Racial Profiling in Montreal

2020· article· en· W3114948580 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe American Review of Canadian Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsConcordia University
Fundersnot available
KeywordsRacial profilingProfiling (computer programming)Status quoPoliticsSociologyRacismPolitical scienceLawGender studiesComputer scienceRace (biology)

Abstract

fetched live from OpenAlex

Racial profiling is an increasingly well-studied problem in Quebec. Efforts to combat this problem, in contrast, are virtually non-existent. Seeking to address this gap, this article examines the long struggle to combat racial profiling in Montreal. This struggle began in earnest in 1979. It saw its most significant achievements between 1984 and 1991 and it saw most of these achievements watered down and rolled back between 1992 and 1997. The struggle was finally reborn in 2008, with an activist-led movement that led to a new strategic plan on racial profiling in 2018. Tracing the history of this struggle serves two purposes. First, it reveals the divergence between the narrow range of measures adopted by the City of Montreal and the wider range demanded by Black, anti-racist, and other progressive actors. Second, it shows that the current strategic plan, while touted as “the most ambitious and far-reaching” effort in the city’s history, is actually a diluted version of the actions taken between 1984 and 1991, actions that did little, if anything, to reduce racial profiling. The present strategic plan signals a failure to learn from the past and points toward a pair of possible futures: one in which the status quo endures and racial profiling continues unabated, and one in which social forces are transformed, driven by the actions of people and organizations that have demanded more from the City, and that proposes a new political vision and a wider set of actions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.454
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.066
GPT teacher head0.382
Teacher spread0.317 · 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