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Record W4285032856 · doi:10.4000/12whw

La diaspora noire au Canada : sociohistoire d’une minorité racialisée et dynamiques contestataires

2022· preprint· fr· W4285032856 on OpenAlexaffabout
Cheikh Nguirane

Bibliographic record

VenueArchipélies · 2022
Typepreprint
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Si le Canada n’a pas connu d’agitations raciales importantes comme celles des villes de Chicago et Notting Hill, les villes de Montréal, Toronto et Halifax ont été le théâtre, au cours des années 1960, de plusieurs luttes antiracistes. Depuis l’adoption des politiques de promotion de la diversité, le Canada reconnaît, quoique timidement, que l’histoire des immigrants, leurs récits et leur contribution font partie de l’histoire du Canada. Néanmoins, l’histoire des Afro-Canadiens demeure encore mal connue du grand public – leur expérience historique étant souvent noyée dans l’histoire officielle du Canada ou réduite à quelques figures emblématiques. Cet article, qui constitue une version de recherches effectuées entre 2013 et 2015, propose de revenir (sans prétendre à l’exhaustivité) sur la formation de la diaspora noire au Canada et quelques grandes étapes de leur lutte contre le racisme systémique et en faveur de la justice sociale. Le domaine de l’éducation apparait comme un véritable laboratoire pour saisir ces dynamiques émancipatrices ainsi que quelques enjeux soulevés dans le contexte du mouvement Black Lives Matter.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0230.012
Scholarly communication0.0060.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2022
Admission routes2
Has abstractyes

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