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Record W4406674434 · doi:10.7202/1115295ar

De la sociologie dessinée à l’utilité de la sociologie

2023· article· fr· W4406674434 on OpenAlexaffvenueabout
Nicolas Sallée, Judith Oliver

Bibliographic record

VenueSociologie et sociétés · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsArtSociologyHumanities

Abstract

fetched live from OpenAlex

Cet article propose un retour réflexif sur la production d’une bande dessinée sociologique consacrée à l’enfermement des jeunes délinquants à Montréal (Se battre contre les murs. Un sociologue en centre jeunesse). Il pointe, pour cela, un constat simple : plus qu’un travail d’illustration, la traduction dessinée de la recherche exige un travail de scénarisation qui peut être assumé par les personnes qui illustrent, mais aussi par d’autres personnes (éditeurs ou éditrices, responsables de collection, etc.). À un premier niveau de lecture, l’article met alors en évidence les rouages concrets de la sociologie dessinée et de la division du travail qu’elle implique, au-delà du seul duo formé par le chercheur et l’illustratrice. Il décrypte, ce faisant, les choix d’écriture — toujours discutables — qu’a exigés ce travail de scénarisation : quel livre cherchions-nous à produire, et avec quelles intentions (analytiques, sinon éthiques et politiques) l’avons-nous fait ? L’article pose dès lors, à un second niveau de lecture, des questions plus générales sur le métier de sociologue, en explicitant les choix, les intentions et, in fine, le rapport à la critique qu’implique toute écriture de la sociologie, de la plus académique à la plus vulgarisée.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.163
Threshold uncertainty score0.325

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0090.046
Scholarly communication0.0130.007
Open science0.0020.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0170.002

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.

Opus teacher head0.711
GPT teacher head0.645
Teacher spread0.066 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes3
Has abstractyes

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