Présentation visuelle des résultats de recherche en sciences sociales : un enjeu de communication non verbale
Bibliographic record
Abstract
Resume francais: Pendant que les moyens de produire et diffuser des materiaux visuels sont rendus disponibles aux chercheurs et chercheuses, on s’interesse peu a problematiser la presentation visuelle des resultats de recherche en sciences sociales. Cette communication non verbale des resultats met en jeu les pratiques concretes et quotidiennes des chercheurs et chercheuses pour construire une recherche avec ces materiaux visuels et leurs consequences sur la presentation des resultats. Les moyens de presenter des contenus visuels mettent notamment en evidence leur manipulation au cours du processus de recherche et leurs insertions dans les documents presentant les resultats de recherche comme une visibilisation et une invisibilisation conjointes des donnees de recherche. Finalement, la visibilite des resultats de recherche et leur visualite permettent de comprendre comment ces materiaux sont visuellement significatifs vis-a-vis de la recherche elle-meme, d’un domaine de recherche en particulier et face a la connaissance scientifique. Abstract: While the means to produce and share visuals are made available to researchers, few scholars problematize the visual presentation of research results in social sciences. At stake are the everyday practices of constructing research with visual materials and their consequences on the presentation of research results. The means to present visual contents highlight the manipulation of visual materials in research processes and their insertion into documents presenting the results of the research both as a visibilization and an invisibilization of research data. In the end, we understand from the visibility and visuality of research results how and why visual materials are visually significant in regard to the research itself, the field of research and scientific knowledge.
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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 | 0.047 | 0.192 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.023 | 0.017 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.030 | 0.008 |
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".