Separate Playgrounds: Surveying the Fields of Girls Media Studies and Boyhood Studies
Bibliographic record
Abstract
I live across the street from an elementary school.During the day, the school is always bustling with activity, young children laughing and yelling as they climb the monkey bars or race across the schoolyard.When I look closer at the children playing, what always surprises me is how this play is separated by gender.The girls dominate the play structure in small tight groups, while the boys chase each other around the sports field.Girls in one area and boys in another, together yet separated.This image of separate playgrounds is refracted in the academic texts I read while I sit in my office, gazing out at the schoolyard.Scholarship on girls is declared to be girls' studies, while research on boys is deemed to be boyhood studies; separate playgrounds, indeed.In 2011, publisher Peter Lang continued this academic segmentation by publishing two engaging anthologies: Annette Wannamaker's (2011) Mediated Boyhoods: Boys, teens and young men in popular media and culture, and Mary Celeste Kearney's (2011) Mediated Girlhoods: New explorations of girls' media culture.Both of these collections are published in Peter Lang's topical new series, Mediated Youth, edited by Sharon Mazzarella.The anthologies are compelling and timely and offer fresh perspectives on the discipline of media studies, edited by key scholars in the fields of boyhood studies and girls' studies.The two texts are rich collections of work that encapsulate a diverse array of content, critical viewpoints, and research methodologies.Each anthology takes
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".