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Record W4385325552 · doi:10.1177/18344909231187018

Bystanders, protesters, journalists: A qualitative examination of different stakeholders’ motivations to participate in collective action

2023· article· en· W4385325552 on OpenAlexaff
Robyn Gulliver, Christian S. Chan, Wendy Wing Lam Chan, Katy Y. Y. Tam, Winnifred R. Louis

Bibliographic record

VenueJournal of Pacific Rim Psychology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsCollective actionInjusticeSocial psychologyCollective identitySocial movementAngerAction (physics)PsychologyThematic analysisSocial identity theoryIdentity (music)Qualitative researchPublic relationsSociologyPolitical scienceSocial groupPoliticsSocial science

Abstract

fetched live from OpenAlex

Both bystanders and journalists can play important roles in mobilizing and supporting social movements. However, there are few empirical studies examining and contrasting their violent and nonviolent collective-action motivations or perspectives on social movement goals. This study presents a comparative analysis of motivations to engage or stand aside from social unrest comparing bystanders ( n = 9) and journalists ( n = 7) motivations against those of protesters ( n = 35). Thematic qualitative analysis of interview data using a Social Identity Model of Collective Action framework examined differences in motivations and goals across each group, as well as the influence of violent protest repertoires on participation behaviors. Identified barriers to participation include bystanders’ lack of issue consensus, low efficacy perceptions, and negative views of violent action. Our results also lend support to the predictive validity of collective identification, anger, and injustice in motivating participation in collective action. Journalists’ collective identity precluded overt protest participation. However, their emotional responses to injustice or violent actions generated tensions between their role obligations and desire to intervene. Implications for future research on collective-action responses to injustice are discussed.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.389
GPT teacher head0.499
Teacher spread0.110 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2023
Admission routes1
Has abstractyes

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