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Record W4392764184 · doi:10.21423/jaawge-v3i1a152

To Mica With Love

2024· article· en· W4392764184 on OpenAlexaffabout
Stephanie Fearon

Bibliographic record

VenueJournal of African American Women and Girls in Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsYork University
Fundersnot available
KeywordsScholarshipGender studiesSociologyCritical race theoryStorytellingThe artsAutoethnographyNarrativeNarrative inquiryBlack maleGirlSpace (punctuation)Race (biology)Political scienceVisual artsPsychologyArt

Abstract

fetched live from OpenAlex

A growing body of research exploring the lives of Black Canadian students largely focuses on achievement and disciplinary outcomes. Such scholarship centers the negative experiences of Black boys, overlooking the quotidian lives of Black Canadian girls in public schools. The lack of educational research engaging Black Canadian girls hinders scholars, educators, and communities from fully reimagining schools for liberation. Drawing from literature and personal stories, this arts-informed autoethnography investigates how I partnered with three Black Canadian girls to reconceptualize their role in research processes. The study relied on disability critical race theory (DisCrit), Black feminist notions of homeplace, and Endarkened storywork to share and analyze narratives of Black girl leadership and innovation. The study revealed how Black researchers and Black Canadian girls used the arts, storytelling, and space to reimagine research processes as homeplace. The study emphasized the need for scholars to engage in research that uphold marginalized Black girls as producers and leaders striving for social change.

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)0.004
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 score0.166
Threshold uncertainty score0.460

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.004
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.1370.044

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 head0.027
GPT teacher head0.366
Teacher spread0.339 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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