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Record W3043797545 · doi:10.14288/cl.v0i237.191626

Maria Campbell's Halfbreed. Reclaiming the Excised Passage

2019· article· en· W3043797545 on OpenAlexaboutno aff
Deanna Reder, Alix Shield

Bibliographic record

VenueOpen Collections · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsBlessingMetisBiographySection (typography)HistoryIndigenousArt historyArtGenealogyArchaeologyComputer scienceWorld Wide WebBiology

Abstract

fetched live from OpenAlex

In a 1989 interview, Métis author Maria Campbell complained to Hartmut Lutz that a section of her autobiography, Halfbreed, first published in 1973, was removed by the publisher against her wishes. During a chance meeting with Campbell in Dublin in 2017, and following Indigenous protocols, Deanna Reder and Alix Shield asked her for permission to search for early versions of Campbell's text. With Campbell's blessing, Alix Shield conducted an archival search for any early material, and discovered the excised passage that revealed that when Campbell was a teenager, she had been raped by RCMP officers. This article includes the found text and discusses the impact of its excision.

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)0.004
metaresearch head score (Gemma)0.027
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.016
Scholarly communication0.0070.006
Open science0.0020.006
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0100.004

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 head0.307
Teacher spread0.284 · 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
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

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueOpen Collections→Same topicIndigenous Health, Education, and Rights→French-language works237,207→