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Record W1505025753 · doi:10.7202/044203ar

Terrain négatif, terrain positif

2010· article· fr· W1505025753 on OpenAlexvenueno aff
Jacques Lucciardi

Bibliographic record

VenueAnthropologie et Sociétés · 2010
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

À partir d’un travail d’enquête en Corse, au sujet des rapports entre la construction des discours politiques et la lecture de la presse quotidienne régionale, j’aborde la question de la nature du « terrain » à l’aide de la métaphore de la main positive et négative dans les peintures pariétales. Ainsi, le terrain est perçu comme un champ de dualités qui structurent chaque niveau de l’enquête, de la délimitation d’une population aux dynamiques de construction des discours politiques qui la concernent. Afin de mettre en évidence ces dualités, j’effectue des entretiens et des observations au sein d’une population d’origine insulaire : élus de la région, journalistes de la presse quotidienne régionale, lecteurs originaires d’un même village. Il s’agit d’étudier les rapports entre les « événements », tels qu’ils apparaissent dans la presse quotidienne régionale, et les discours des divers acteurs impliqués dans et par ces événements. Les dynamiques à l’oeuvre dans la production des événements et des discours peuvent alors être comprises comme des effets de la coexistence de consensus contradictoires qui émergent dans le cadre d’une société d’interconnaissance.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.011
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0300.001

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.

Opus teacher head0.127
GPT teacher head0.508
Teacher spread0.381 · 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
Published2010
Admission routes1
Has abstractyes

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