Mapping transgender policyscapes: A policy analysis of transgender inclusivity in the education system in Ontario
Bibliographic record
Abstract
In this paper we draw on Mettler’s concept of the policyscape and apply it to an examination of policy-making processes and events as they pertain specifically to an analysis of transgender inclusivity and gender diversity in the Ontario context. We employ Ball’s focus on policy as text and policy ensembles alongside Bailey’s employment of policy dispositifs to map key events that characterize important legislative developments that define the Ontario education policy landscape with regards to addressing gender identity and gender expression as a basis for anti-discrimination. We situate particular events such as the GSA (Gay Straight Alliance or Gender and Sexuality Alliance) and sex education controversies within a broader context of trans activism, which we identify as pointing to quite specific contingencies that characterize the Ontario policyscape. Overall, the paper extends a consideration of the specificities of the Ontario case in Canada to a broader reflection on the utility of the policyscape as a crucial concept for making sense of the relevance of more general characteristics of a spatially-focused trans informed policy analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".