Gender and sexually minoritized system educational leaders and the team-based development of equity policies: A framework
Bibliographic record
Abstract
Inequities experienced by minoritized groups are one of the greatest challenges facing education systems today. Accordingly, system educational leaders are responsible for developing equity-related policies that have far-reaching impact on school systems, which situates these leaders at the forefront of delivering solutions that improve outcomes for minoritized students. Yet, because of extant oppressive structures that reinforce hegemonic power norms and exacerbate social inequities, educational leaders are often complicit in perpetuating inequities. This is complicated further by the fact that most of them are dominantly located (i.e., White, cisgender, male, heterosexual), which results in a limited frame of reference when making decisions that impact minoritized groups. It is salient, then, to seek more understanding about how equity-related policymaking takes place in the context of system educational leadership teams comprised of both dominantly located and minoritized leaders. More specifically, because contending with inequities experienced by gender and sexually minoritized (GSM) individuals is often viewed as a lower priority relative to other equity-deserving groups, focusing on policymaking through the frame of this specific minoritized group is particularly relevant. This article presents a conceptual framework that establishes coherence between the various facets of team-based, equity-related policymaking, which include team dynamics, the degree to which leaders adopt equity-oriented leadership practices, and the unique contexts in which the policy is crafted. Moreover, the framework highlights how these policymaking factors are influenced by a coalescence of the identities; lived experiences; and dispositions, beliefs, and assumptions of the dominantly located and GSM leaders involved in the policymaking process.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".