A Queer Critical Media Literacies Framework in a Digital Age
Bibliographic record
Abstract
Abstract Media literacy skills are focal for many educators across the globe in an age of ubiquitous access to the Internet and the rapid circulation of digital texts. A critical media literacies perspective is often a key element in teaching adolescents to read a range of texts. A queer critical media literacies pedagogy supports a social justice agenda aimed at addressing inequalities in education for youths who identify as lesbian, gay, bisexual, transsexual, and queer (LGBTQ+), with the + accounting for other identities, such as asexual, agender, and questioning. Queer theories provide the basis of a new pedagogical model aimed at empowering educators to guide young adolescents in identity formation as they navigate a range of content. The model is presented as a queer critical media literacies framework aimed at directly supporting the work of teachers in classrooms, including illustrative key questions, learning experiences, and related teaching resources.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.007 | 0.037 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".