MétaCan
Menu
← Back to cohort
Record W4407590199 · doi:10.62859/9781917503327

Léa Roback

2025· book· en· W4407590199 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Who was Léa Roback? And what can we learn from activism? Léa Roback (1903-2000) gained renown for her seven decades of activism in Quebec, particularly championing union rights and women rights. Yet, despite her significant accomplishments no English-language biography exists. In our current geo-political climate, marked by polarization and lack of dialogue, documenting Roback's ability to transcend linguistic, religious, cultural, and class boundaries in pursuit of social justice is inspiring. This biography, based on interviews between Roback and filmmaker Sophie Bissonette, sociologist Nicole Lacelle, journalist Merrily Weisbord and others, promises to engage students, educators in social justice-oriented fields, Equity Studies, Gender Studies, Education Studies, Canadian Studies, Canadian History courses and all those who seek justice and enthusiasm from a life-long human rights activist.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.908
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0920.035

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 head0.034
GPT teacher head0.253
Teacher spread0.219 · 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.

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicLinguistics and Discourse Analysis→French-language works237,207→