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Record W1568920028 · doi:10.22230/cjnser.2010v1n1a2

Motivations and Benefits of Student Volunteering: Comparing Regular, Occasional, and Non-Volunteers in Five Countries

2010· article· en· W1568920028 on OpenAlexvenueaboutno aff
Karen Smith, Kirsten Holmes, Debbie Haski‐Leventhal, Ram A. Cnaan, Femida Handy, Jeffrey L. Brudney

Bibliographic record

VenueCanadian journal of nonprofit and social economy research · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsPopularityAltruism (biology)Value (mathematics)Service-learningHigher educationPsychologyPublic relationsPolitical scienceEconomic growthSocial psychologyPedagogyEconomics

Abstract

fetched live from OpenAlex

Programmes targeting student volunteering and service learning are part of encouraging civic behaviour amongst young people. This article reports on a large scale international survey comparing volunteering amongst tertiary students at universities in Australia, Canada, New Zealand, the United Kingdom, and the United States of America. The data revealed high rates of student volunteering and the popularity of occasional or episodic volunteering. There were strong commonalities in student volunteering behaviour, motivations and benefits across the five Western predominately English-speaking countries. Altruism and self-orientated career motivations and benefits were most important to students; however volunteering and non-volunteering students differed in the relative value they attached to volunteering for CV-enhancement and social factors.

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 score0.005
Threshold uncertainty score0.011

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.354
Teacher spread0.284 · 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

Citations163
Published2010
Admission routes2
Has abstractyes

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Same venueCanadian journal of nonprofit and social economy researchSame topicNonprofit Sector and VolunteeringFrench-language works237,207