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Record W2109766567 · doi:10.1023/a:1008903032393

Public Perception of “Who is a Volunteer”: An Examination of the Net-Cost Approach from a Cross-Cultural Perspective

2000· article· en· W2109766567 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueVOLUNTAS International Journal of Voluntary and Nonprofit Organizations · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsYork University
Fundersnot available
KeywordsSample (material)PerceptionPsychologyPublic economicsMarketingSocial psychologyBusinessEconomics

Abstract

fetched live from OpenAlex

Our aim is to enhance the knowledge regarding how the public assess and rate volunteerism. We begin by first developing the model for understanding the potential use of the net-cost concept in eliciting the public’s subjective perceptions on the extent to which certain activities are perceived as volunteerism. Four hypotheses relevant to the use of the net-cost concept are developed. We developed a questionnaire consisting of 50 case scenarios and applied it in Canada, India, Italy, Netherlands, and Georgia and Philadelphia in the United States, each with a sample of 450 adults or more. With one exception, our net-cost hypotheses are supported, suggesting that the public perception of volunteering is strongly linked with the costs and benefits that accrue to the individual from the volunteering activity, and that this result holds true across different cultures. Finally, we suggest directions for future research that can shed further light on the relationship between net cost and public good.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.319
Teacher spread0.290 · 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