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Record W7008186391

Book Review: #BLACKINSCHOOL

2024· article· en· W7008186391 on OpenAlexaff

Bibliographic record

VenueJournals @ The Mount (Mount Saint Vincent University) · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsYork University
Fundersnot available
KeywordsNatural (archaeology)Work (physics)Product (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Her research draws on Black storytelling traditions to explore the ways that Black mothers and educational institutions partner to support Black student wellbeing.Stephanie uses literary and visual arts to communicate, in a structured, creative, and accessible form, insights gleaned from stories shared by Black mothers and their families.Her publications have appeared in several scholarly journals, including Canadian Journal for the Study of Adult Education, Canadian Review of Sociology/Revue canadienne de sociologie, and Journal of African American Women and Girls in Education.Stephanie has worked nearly fifteen years in public education systems assuming leadership positions in France, Guadeloupe, and Canada.Most recently, she was the program coordinator for the Equity, Anti-Racism and Anti-Oppression Team and the Model Schools for Inner Cities Department at the Toronto District School Board.In this role, Stephanie provided leadership to administrators and system leaders in implementing policies and practices that promote student academic achievement, wellbeing, and belonging in schools.

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)0.007
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: Review · Consensus signal: Review
Teacher disagreement score0.242
Threshold uncertainty score0.809

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.2420.166

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 head0.017
GPT teacher head0.211
Teacher spread0.194 · 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
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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