« Nous sommes moins visibles aux yeux des gens »: Donner une place centrale aux préadolescentes militantes par rapport au reste des citoyens
Bibliographic record
Abstract
In recent years, there has been significant attention paid to girls who are engaged in activism. When we look at who has been recognized for their activism, however, mainstream exposure to girl activists has primarily included teenagers and youth. Girls of the tweenhood age, for example, are also engaged in activism but their efforts go largely unnoticed or face patronization. Instead of being taken seriously, the activism of many tween girls is: (1) clouded by the constructed inherent innocence of childhood, (2) entangled with the construction of (white) tween girlhood as a time of frivolity and fun, and (3) marginalized due to the adult-centric nature of citizenship in Canada and the United States. As the very structures that would traditionally allow for adults to make their voices heard are not designed for the equitable participation of children, tween girls are required to participate in creative ways. This article, therefore, frames tween girls’ activism as citizenship and offers opportunities to both reconsider and validate these varied activist practices as legitimate democratic participation. Tween girls are already shaping their social, cultural, and political worlds, asserting that they belong and deserve to be seen, heard, and taken seriously. The lenses of societal and feminist responses need to be reoriented and refocused to see it.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.012 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 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".