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Record W2911185672 · doi:10.1111/1468-4446.12627

Curriculum requirements and subsequent civic engagement: is there a difference between ‘forced’ and ‘free’ community service?

2019· article· en· W2911185672 on OpenAlexaff
Ailsa Henderson, Steven D. Brown, S. Mark Pancer

Bibliographic record

VenueBritish Journal of Sociology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsCivic engagementService (business)Service-learningCommunity engagementDuration (music)CurriculumPopulationPsychologyPublic relationsMedical educationPolitical scienceBusinessSociologyPedagogyMarketingMedicineDemography

Abstract

fetched live from OpenAlex

Despite figures showing the growth of mandatory community service programmes, there is mixed empirical evidence of their effectiveness. This paper addresses the relationship of mandated community service to one of its purported aims: subsequent volunteerism. It compares current volunteerism among four university student cohorts: those doing no service in secondary school, those volunteering with no requirement, those volunteering both before and after the introduction of a requirement, and those introduced to service through a requirement. The analysis indicates that (1) students who were introduced to service through a mandated programme exhibit current levels of engagement no greater than non-volunteers; (2) this relationship stems largely from the different service experiences of our four cohorts and relates to the fact that service satisfaction and duration, as well as background variables account for current levels of civic engagement. The findings suggest that mandatory service programmes might well be failing the very population they seek to target, particularly in weaker, less structured programmes.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.321
Teacher spread0.266 · 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 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

Citations9
Published2019
Admission routes1
Has abstractyes

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