Access, Inclusion, Climate, Empowerment (AICE): A Framework for Gender Equity in Market-Driven Education
Bibliographic record
Abstract
We present a framework for conceptualizing gender equity, designed around four equity components: Access, Inclusion, Climate, and Empowerment (AICE). Our examination of these components in the current market schooling climate, with particular reference to the situation in Ontario, identifies some significant equity costs of market-driven education, including invisibility of systemic discrimination, co-option of gender equity initiatives to serve market objectives, failure to consider diversity and relations of power in educational practices, increased risks of sexual harassment, and increased barriers to social change. AICE equips educators with an analytical tool to conceptualize gender equity in a market-driven schooling climate. Les auteures proposent de conceptualiser le traitement equitable des sexes a l’aide d’un schema forme de quatre elements : acces, inclusion, climat et habilitation. L’analyse de ces elements dans le contexte scolaire actuel, en particulier en Ontario, devoile d’importants couts inherents a l’enseignement axe sur le marche, dont l’invisibililite de la discrimination systemique, l’assimilation aux objectifs du marche des initiatives en matiere d’equite entre les sexes, l’occultation de la diversite et des relations de pouvoir dans les pratiques pedagogiques, les risques accrus de harcelement sexuel et la multiplication des obstacles au changement social. Le schema donne aux enseignants un outil analytique leur permettant de conceptualiser le traitement equitable des sexes dans un contexte educatif axe sur le marche.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".