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Record W2060638714 · doi:10.1177/0002764211419357

Picturing Protest

2011· article· en· W2060638714 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAmerican Behavioral Scientist · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsUniversity of British ColumbiaWestern University
Fundersnot available
KeywordsCollective actionIndigenousNewspaperAction (physics)Social movementSociologyGovernment (linguistics)Media studiesState (computer science)Public opinionMass mediaPolitical sciencePoliticsLawLinguistics

Abstract

fetched live from OpenAlex

Images of collective action shape public understanding of social movement campaigns and issues. Modern media includes more images than ever before, and these images are remembered longer and are more likely to elicit emotional responses than are textual accounts. Yet when it comes to media coverage of collective action, existing research considers only the written accounts. This means that little is known about the extent to which images of collective action events conform to or diverge from the “protest paradigm,” a pattern of reporting found in articles that tends to marginalize protesters and legitimizes authorities. The authors address this gap by analyzing newspaper photographs of one of the most significant recent cases of Indigenous-state conflict in North America—the 1990 “Oka Crisis.” This 78-day armed standoff between Indigenous peoples and Quebecois and Canadian authorities was sparked by the attempted expansion of a golf course onto Mohawk territory. The mass media produced thousands of articles and photographs in their coverage of the event. This article uses these photographs to assess the manner in which images frame collective action and collective actors. The authors find that images of collective action frame these events differently and in a more nuanced way than do textual accounts. For example, while challengers are just as likely to be shown in images of collective action, they are less likely to be specifically named. In addition, officials are more likely to be shown in dominant positions, but certain groups of officials (particularly government representatives) are also the most likely to be shown as emotional and angry. These findings illustrate the sometimes conflicting messages depicted in images of collective action.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.999

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.148
GPT teacher head0.295
Teacher spread0.146 · 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