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Record W4311185571 · doi:10.4000/edc.15343

Controverse Blitzchung : étude de l’activisme fan au sein d’une communauté de joueurs de jeux vidéo

2022· article· fr· W4311185571 on OpenAlexaff
Maude Bonenfant, Patrick Deslauriers, Jérémie Pelletier-Gagnon

Bibliographic record

VenueEtudes de communication/Études de communication · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet article s’intéresse à la manière dont l’activisme fan de certains leadeurs de la communauté des joueurs a participé à la construction du discours et influencé le mouvement de contestation dans le contexte de la « controverse Blitzchung ». Lors de cet événement, débuté le 6 octobre 2019, Blitzchung, un joueur du jeu vidéo Hearthstone, a scandé un message pro-Hong Kong en direct suite à sa victoire lors d’un tournoi. Deux jours plus tard, l’éditeur Blizzard l’a sanctionné, ce qui a entraîné plusieurs actions en ligne et sur le terrain en guise de protestation pour défendre le joueur et dénoncer le pouvoir de l’État chinois. Nous démontrons la manière dont l’activisme fan a participé à la construction du discours et a influencé le mouvement de protestation lors des événements entourant cette polémique.

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 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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0090.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.324
Teacher spread0.271 · 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 teacher head, not a consensus.

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
Published2022
Admission routes1
Has abstractyes

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