Challenging the lack of representation in mainstream media through the establishment of inclusive digital spaces
Bibliographic record
Abstract
Media representations of marginalized people are a growing concern given the state of the current social climate. The origin of intolerance stems from a lack of exposure and knowledge and as a result, marginalized groups struggle to maintain adequate space and representation in mainstream media. This reflects a lack of inclusivity, diversity and safe spaces. Establishing inclusive digital environments that promote the equality of peoples rather than perpetuating stereotypes is a vital way to achieving visibility and growth among marginalized and underrepresented people. INFLUENCE Magazine is a digital publication that is committed to equality, representation and opportunity. By providing a safe space for marginalized and underrepresented sectors of society to express every aspect of their identity, art and lived experiences, INFLUENCE Magazine fosters a positive environment for artists and individuals to freely express themselves.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.024 | 0.016 |
| Open science | 0.002 | 0.029 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".