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Record W2807388476 · doi:10.1075/sl.17008.ham

From #[Je]F suis Charlie to #JeSuisCharlie

2018· article· en· W2807388476 on OpenAlex

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

VenueStudies in Language · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersUniversität zu Köln
KeywordsSubject (documents)SentenceLinguisticsMeaning (existential)Reading (process)Focus (optics)SolidaritySociologyPhilosophyComputer scienceEpistemologyPolitical scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Je suis Charlie was used over 619.000 times in the two days that have followed the attack of Charlie Hebdo and has regularly been taken up in both written and spoken forms since. A number of variants of this meme (i.e. Nous sommes tous (des) Charlie ) have also emerged among French speakers. We argue that this is primarily related to the fact that the structure of Je suis Charlie actually clashes with its meaning. Whereas its word order and default rightmost sentence stress are compatible either with an all-focus reading or a narrow focusing of Charlie , the solidarity/empathy message it communicates suggests that its subject is narrowly focused. We propose that two strategies have emerged to solve this conflict: (i) various alternative forms have appeared that allow proper subject focusing and (ii) speakers have reinterpreted the original structure so as to pragmatically retrieve the (additive) focused nature of the subject.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.054
GPT teacher head0.323
Teacher spread0.269 · 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