MétaCan
Menu
Back to cohort
Record W7004845309

9781773854939_OA.pdf

2023· other· en· W7004845309 on OpenAlexaboutno aff

Bibliographic record

VenueOAPEN (The OAPEN Foundation) · 2023
Typeother
Languageen
FieldArts and Humanities
TopicMedical History and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousWork (physics)MultitudeAgency (philosophy)Domestic violence
DOInot available

Abstract

fetched live from OpenAlex

In Canada, a woman is killed by her intimate partner every six days. Alberta has one of the highest rates of domestic violence in the country. Starting in the 1970s, Alberta women’s shelters have assisted women in crisis. Much more than a safe place to sleep, shelters work to prevent violence through education and training, connect people and communities, and support the complex needs of survivors through a multitude of services. We Need to Do This is the story of Alberta women's shelters. Based on dozens of in-depth interviews, it traces the evolution of a progressive social movement in a traditionally conservative province. These are the stories of women whose voices may otherwise never have been heard: entry-level workers at fledgling shelters battling the assumption that their facilities would create crime, small-town shelter directors forced to self-censor or lose communityand financialsupport, Indigenous women fighting to serve their sisters in Indigenous spaces. Beginning with the women who founded the first shelters, and continuing through the establishment of the Alberta Council of Women's Shelters to the present day, We Need to Do This is a story of hope and survival for the women’s shelter movement and for the mothers, sisters, aunts, cousins, and daughters it continues to serve.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.814
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9870.988

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 head0.044
GPT teacher head0.249
Teacher spread0.204 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueOAPEN (The OAPEN Foundation)Same topicMedical History and InnovationsFrench-language works237,207