Understanding the Lived Experiences of the members of the Society for the Advancement of Biology Education Research through Collins' Matrix of Domination Framework
Bibliographic record
Abstract
Professional science societies stand at the intersection of science, education, and research, providing crucial professional development and career opportunities for scientists. Their structures and policies can either promote more equitable ideologies, practices and outcomes or deepen existing disparities within science. In recent years, many societies have implemented diversity statements and initiatives, but few studies have examined their actual impact on membership composition and the experiences of their minoritized members. Critical education scholars emphasize the importance of examining these experiences through frameworks that center their voices, acknowledge institutional racism, and address the power imbalances that exclude marginalized groups. This study uses the matrix of domination framework (Collins, 1990) and its four domains of power (structural, disciplinary, interpersonal, and cultural/hegemonic) to investigate the perceptions and experiences of inclusion/exclusion of the members of the Society for the Advancement of Biology Education Research (SABER). We identified factors that contribute to and detract from the society's equity goals by analyzing members' experiences at different systemic levels. By framing members' experiences through the lens of dimensions of power, we reveal relationships and structures that may have otherwise remained invisible, offering new insights into strategies that can better aid professional societies toward their equity goals.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.036 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| 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 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".