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Record W4386293032 · doi:10.4000/communication.17160

Le savoir des communautés de hackers. Le digital comme objet de passion, domaine de niche et vision avant-gardiste

2023· article· fr· W4386293032 on OpenAlexvenueno aff
Lisa Bolz

Bibliographic record

VenueCommunication · 2023
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanitiesHackerComputer science

Abstract

fetched live from OpenAlex

Le Chaos Computer Club (CCC) est une communauté de hackers allemands créée en 1981 et connue pour sa promotion de formes d’activisme et pour ses activités aux frontières de la légalité. Elle est aujourd’hui devenue une institution parfois sollicitée par le Bundestag allemand. En s’appuyant sur un corpus qui n’a pas encore été étudié, celui du magazine Datenschleuder, un old media (voir Magaudda et Balbi pour cette terminologie) investi par une nouvelle génération d’acteurs du hacking, l’article propose une analyse de l’image que le CCC se fait de lui-même, surtout dans sa première phase, en insistant explicitement sur sa conception non déterministe des transformations digitales. À la lumière de cette analyse, il est démontré que cette communauté de « bons hackers » contribue à mettre au jour des dysfonctionnements et à lutter contre certaines formes de cybercriminalité, ce qui a amplement mené, en Allemagne, au développement de normes et de règles de hacking, à l’activisme pour la liberté d’information et à l’éducation du public sur les technologies informatiques.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0090.021
Scholarly communication0.0120.010
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.002

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 head0.260
GPT teacher head0.359
Teacher spread0.099 · 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.

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
Published2023
Admission routes1
Has abstractyes

Explore more

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