Bibliographic record
Abstract
When analyzing young people’s media projects, it is easy to get excited about “youth voice” as a site of free expression and social critique. Tempting as this is, media scholars, as well as young producers and adult mentors, note the varied, often contradictory, voices and interests at play within youth videos, photography exhibitions, and other media experiments. Here, I focus on a specific manifestation of multivocality in youth media discourse. That is, heavy use of “reported speech,” a linguistic term to describe moments of interaction in which speakers quote, paraphrase, or otherwise invoke other people’s words. Young media producers use reported speech in striking ways to negotiate authority over their own projects, animating an interactive process I call “crowded talk,” with implications for multiliteracy theory and practice. AU-DELA DE LA LITTERATIE ET DE LA VOIX DANS LA PRODUCTION MEDIA DES JEUNES RESUME. Lorsque nous analysons les projets mediatiques des jeunes, il est facile de s’enthousiasmer a propos de la « voix des jeunes » comme foyer de liberte d’expression et de critique sociale. Meme si cet enthousiasme est invitant, les chercheurs en media, ainsi que les jeunes producteurs et les mentors adultes, soulignent la diversite, et souvent la contradiction, des voix et des interets qui entrent en jeu dans les videos, les expositions de photos et les autres experiences mediatiques des jeunes. Ici, je mets l’accent sur une manifestation precise de la multiplicite des voix dans le discours des medias des jeunes. C’est-a-dire, l’utilisation excessive d’un « discours rapporte », un terme de linguistique qui decrit les moments d’interaction ou les orateurs citent, paraphrasent ou rappellent d’une autre facon les mots d’autres personnes. Les jeunes producteurs de medias utilisent le discours rapporte de facon saisissante afin de revendiquer une autorite autour de leurs propres projets, animant un processus interactif que j’appelle crowded talk, (conversation chargee) qui a des repercussions sur la theorie et la pratique de la multilitteratie. Literacy is an omnipresent term in youth media research. The arguments circulating around this term and its various permutations (e.g., multiliteracies, popular literacy, critical literacy, media literacy) constitute a full-blown
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".