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Record W2412767153 · doi:10.1111/josi.12165

The “Activist Identity” and Activism across Domains: A Multiple Identities Analysis

2016· article· en· W2412767153 on OpenAlexaff
Winnifred R. Louis, Catherine E. Amiot, Emma F. Thomas, Leda Blackwood

Bibliographic record

VenueJournal of Social Issues · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical activismSocial activismPoliticsNationalismIdentity (music)Political scienceSociologyEnvironmentalismGender studiesLaw

Abstract

fetched live from OpenAlex

Two correlational studies of activists examined the association between belonging to community organizations or groups and sustained activism within a particular domain. In Study 1 ( N = 45) larger activist networks, controlling for activist identification and greater political knowledge, were associated with stronger activism intentions. In Study 2 ( N = 155), larger Time 1 peace activism social networks were associated with more Time 2 peace activism and, via Time 2 activism, with sustained activism at Time 3. In contrast, Time 1 nationalist and party political identities were inhibiting factors of peace activism at Time 2, and indirectly at Time 3. In addition, larger peace activism networks at Time 1 were associated with greater international human rights activism and Christian activism at Time 3, but not as consistently with other forms of cross‐domain activism. The possible organizing principles for these interrelationships 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.412
Teacher spread0.381 · 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 source (direct Gemma or distilled Codex), 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

Citations87
Published2016
Admission routes1
Has abstractyes

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