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Record W3121504783 · doi:10.7202/1074378ar

Les documentalistes de l’audiovisuel public : sortir de l’ombre une profession, révéler les archives audiovisuelles

2021· article· fr· W3121504783 on OpenAlexvenueno aff
Anna Tible

Bibliographic record

VenueJournal of the Canadian Historical Association · 2021
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Les professionnel.le.s de la documentation audiovisuelle participent activement aux créations audiovisuelles à base d’archives, des émissions actualités aux talk-shows, dès les débuts de la télévision publique européenne. De 1952 à aujourd’hui, les documentalistes audiovisuel.le.s de l’audiovisuel public français, en particulier dans le cadre de l’Institut National de l’Audiovisuel (INA) depuis 1974, n’ont eu de cesse de chercher à partager les connaissances sur les contenus et supports audiovisuels qui ont marqué l’histoire des médias français de la deuxième moitié du XXe siècle. Les professionnel.le.s ont longtemps construit leur savoir-faire, leurs outils et leurs méthodologies de travail de maniére autonome, à l’écart de toute volonté institutionnelle, afin de sortir de l’ombre les archives audiovisuelles. Cet article, qui s’intègre dans le cadre d’un doctorat en Information- Communication sur l’histoire de la profession de documentaliste audiovisuel, questionnera donc l’évolution du rôle de ces professionnel.le.s, dans la mise en lumière des archives auprès de publics toujours plus divers. Les documentalistes, interlocuteur.ice.s essentiel.le.s des différents usager.e.s des archives, doivent en effet inscrire leurs pratiques et méthodologies de travail dans le cadre de productions collectives, et dans le contexte d’une valeur de plus en plus marchande des sources audiovisuelles.

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)0.011
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.004
Science and technology studies0.0170.020
Scholarly communication0.0260.019
Open science0.0020.011
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0260.009

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 head0.146
GPT teacher head0.296
Teacher spread0.151 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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