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Record W4403267209 · doi:10.4000/12dkk

L’enfermement dans les pratiques de big data : une interprétation par la théorie sociale critique

2024· article· fr· W4403267209 on OpenAlex
Frantz Rowe, Ojelanki Ngwenyama

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTerminal · 2024
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Les géants du capitalisme numérique exploitent des pratiques de big data reposant sur la datafication de nos comportements, sur l’accès permanent à ces données et sur leur traitement par apprentissage automatique. Nous nous enfermons dans ces pratiques et les plateformes associées sans en être pleinement conscients. Cet article propose une théorie de la dynamique causale de cet enfermement représentée à la fois par des boucles de renforcement et synthétisée par trois propositions. L’idéologie de la technique (Marcuse, 1968) conduit le développement d’une fausse conscience (Heidegger, 1954) qui conditionne l’enfermement numérique et conduit à des marchandages faustiens. Tant la fausse conscience, que cet enfermement et les marchandages faustiens sont l’objet de boucles causales de renforcement délétères et inter-reliées constituant une explication plausible de la diminution des libertés des utilisateurs du numérique.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.237
GPT teacher head0.388
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