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Record W6980256791

Blackness, exclusion, and the law in the history of Canadaâs public schools, Ontario and Québec, 1850âpresent

2018· other· en· W6980256791 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipPublic historyContext (archaeology)Representation (politics)InstitutionLegal historyReputationUnderground RailroadLegislative history
DOInot available

Abstract

fetched live from OpenAlex

With an eye towards current practices of anti-Black schooling discrimination, this project theorizes the ways that public schooling violence throughout Canada impacted the lives of Black families and their children for over 100 years beginning in the early 19th century. A number of scholars have documented the history of schooling violence in Ontario and Nova Scotia. This project builds upon such scholarship and locates Montréal within this history. Although this project does provide a historical landscape for the history of anti-Black violence within the institution of public schooling, this project also proposes a grammar for Canadian anti-Black racism, as well as characterizes a more robust critical race theory within a Canadian historical context than has been previously theorized by legal scholars and historians. Importantly, this project uses the backdrop of 19th-century Black migration to Canada, prompted at its apogee by the 1850 Fugitive Slave Act, to narrate a more nuanced representation of the Underground Railroad and debunk its reputation as a terminus of safety and freedom for Black refugees. Rather, I propose that the history of public schooling discrimination, coinciding with Black migration, best illuminates Canada’s tradition of anti-Black violence historically.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.279
Threshold uncertainty score0.837

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 studies0.0480.023
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.022
GPT teacher head0.212
Teacher spread0.191 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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