Let the Boys Sing and Speak: Masculinities and Boys' Stories of Singing in School
Bibliographic record
Abstract
This paper includes narrative material that has been adapted from: What It's All About, a one-act play; Yo, Fag!, a poem, and The Practice, a mixed-perspective narrative; taken from Chapter Five of the doctoral dissertation: Adler, A. ( 2002), A case study of boys' experiences of singing in school.Doctoral dissertation, University of Toronto."It looked like you were sleeping or something.""I was listening to the choir," replies George."They were singing ... my song.""Well, you can't lose focus like that during the game.It's dangerous," replies Brent."And ditch that long face as well.YOU'RE the one who wanted to ditch choir.And besides, we haven't got time for both, anyway."The whistle sounds ... The drums beat... It's time to play the game.On whose whistle do YOU run, my boy?To whose drum do YOU march?In the yard, A boy stands quietly staring At the music room window, Waiting ... The bell sounds -He's missed his chance.His voice recedes Silently to its own Tumultuous depths As he walks, invisible, to class.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.032 | 0.030 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".