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Record W2964675301 · doi:10.1017/s0008423918000914

Engaging Youths across the Education Divide: Is There a Role for Social Capital?

2019· article· en· W2964675301 on OpenAlexaff
Livianna Tossutti

Bibliographic record

VenueCanadian Journal of Political Science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsBrock University
Fundersnot available
KeywordsSocial capitalVotingTurnoutPoliticsSocial engagementSocial mobilityCivic engagementSocial trustPolitical scienceSocial reproductionPolitical capitalSocial psychologySociologyPsychology

Abstract

fetched live from OpenAlex

Abstract This study draws on the 2013 General Social Survey to investigate whether social capital is positively associated with the political participation and engagement of 15- to 24-year-old Canadians. It also assesses whether social capital can help overcome the participation gap between youths with different educational qualifications. Trust in family was the only social tie that was positively associated with the turnout of eligible voters in federal and municipal elections. Associational involvements and generalized trust in strangers were more frequently related to informal political activism and an interest in politics. Online social connections were unrelated to any measure of participation and engagement. Some forms of social capital can help address the marginalization of youths from formal and informal politics, but tertiary education is most closely associated with voting.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.737

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.361
Teacher spread0.331 · 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 designObservational
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

Citations1
Published2019
Admission routes1
Has abstractyes

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