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Record W3112607857 · doi:10.1177/1368430220985208

Activism in the time of COVID-19

2021· article· en· W3112607857 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

VenueGroup Processes & Intergroup Relations · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCollective actionNormativeAngerAction (physics)Coronavirus disease 2019 (COVID-19)Social psychologyPandemicIsolation (microbiology)PsychologyIdentification (biology)Political economyPolitical scienceSociologyCriminologyPoliticsLaw

Abstract

fetched live from OpenAlex

In many countries, COVID-19 has amplified the health, economic and social inequities that motivate group-based collective action. We draw upon the SIRDE/IDEAS model of social change to explore how the pandemic might have affected complex reactions to social injustices. We argue that the virus elicits widespread negative emotions which are spread contagiously through social media due to increased social isolation caused by shelter-in-place directives. When an incident occurs which highlights systemic injustices, the prevailing negative emotional climate intensifies anger at these injustices as well as other emotions, which motivates participation in protest actions despite the obvious risk. We discuss how the pandemic might shape both normative and non-normative protests, including radical violent and destructive collective actions. We also discuss how separatism is being encouraged in some countries due to a lack of effective national leadership and speculate that this is partially the result of different patterns of social identification.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.650
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.352
Teacher spread0.319 · 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