Sports equity: a new BJSM e-Edition brings the fundamentals back into focus
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
> Change your leaves, keep intact your roots > > –Victor Hugo Throughout history and across cultures, nearly all human societies have constructed systems of privilege and power that oppress, exploit and disadvantage some, while empowering others.1 Across sectors, the powerful have engineered these systems to achieve step-change economic gains at the expense of the oppressed. In addition to wealth, systems of oppression also generate non-material benefits for those on the weighty side of the power imbalance. Consciously or not, as micro-aggressions and macro-aggressions from the advantaged are dealt down the power gradient to the disadvantaged, social advancement opportunities and recognition disproportionately benefit the dominant group.1 The key here is that people actively thought this through . These intentionally designed systems divide society into a dystopian hierarchy based on race/ethnicity, gender, perceived ability, wealth, age and more, despite the fundamental human rights all people are equally due. As clinicians and academics, we have the opportunity to consciously and deliberately expose and dismantle societal biases in our field of Sport and Exercise Medicine (SEM). While …
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.
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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it