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Record W3165541898 · doi:10.3167/cont.2021.0902of

A Penchant for Protest?

2021· article· en· W3165541898 on OpenAlexaffabout
Randle J. Hart

Bibliographic record

VenueContention · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsPoliticsOddsIdentity (music)General Social SurveySocial psychologyPolitical activismSociologyExploratory researchSurvey data collectionGender studiesPolitical scienceLogistic regressionPsychologySocial scienceLaw

Abstract

fetched live from OpenAlex

Abstract Much has been made of the Millennial generation's seemingly low rates of political participation. Some argue that this generation is politically apathetic, while others suggest that Millennials have eschewed traditional politics in favor of protest as a means of political participation. Drawing on Canada's 2013 General Social Survey (Cycle 27, Social Identity), I employ an exploratory latent class analysis to determine whether the Millennial generation can be usefully categorized according to their participation in various forms of political, civic, and social movement activities. I then use binary logit regression to determine how well the biographical availability hypothesis explains Millennial politics. This research reveals that Canadian Millennials may be grouped into four categories: the politically unengaged , the politically expressive , the civically engaged , and activist . Support for the biographical availability hypothesis is mixed. As expected, students are more likely to be activists and parenthood reduces the odds of being politically expressive or an activist, but home ownership does not decrease the chances of Millennials being politically engaged and increases the chances of being civically engaged. Younger Millennials (ages 15–24) are much more likely to be politically unengaged compared to older Millennials (ages 25–34).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.213

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 studies0.0000.000
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 head0.077
GPT teacher head0.374
Teacher spread0.297 · 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 designTheoretical or conceptual
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

Citations2
Published2021
Admission routes2
Has abstractyes

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