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Record W3121462619

Economic Evaluation: The Effect of Money and Economics on Attitudes about Volunteering

2008· preprint· en· W3121462619 on OpenAlexaff
Jeffrey Pfeffer, Sanford E. DeVoe

Bibliographic record

VenueRePEc: Research Papers in Economics · 2008
Typepreprint
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMediationArgument (complex analysis)PaymentMechanism (biology)EconomicsPublic economicsSocial psychologyPositive economicsMicroeconomicsActuarial scienceMonetary economicsPsychologySociologyFinanceSocial science
DOInot available

Abstract

fetched live from OpenAlex

Recent research shows that hourly payment affects decisions about time use in ways that disfavor uncompensated activities such as volunteering. This paper extends that argument by showing that the activation of money and economics as aspects of a person's self-concept is one mechanism possibly producing these results. Study 1 showed that employed adults explicitly primed to think about their own time in terms of money were less willing to volunteer compared to those primed to think about another person's time in terms of money, illustrating the importance of the self-concept in the economic evaluation of time. Mediation analyses showed that participants' view of themselves as economic evaluators fully accounted for both the effect of the manipulation and variation in prior experience with hourly payment on willingness to volunteer. Study 2 showed the undergraduates supraliminally primed with either money or economic concepts were less willing to volunteer their time. The findings suggest that economic evaluation is one causal mechanism affecting attitudes about time use.

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)0.004
metaresearch head score (Gemma)0.017
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 score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.043
GPT teacher head0.373
Teacher spread0.330 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicNonprofit Sector and VolunteeringFrench-language works237,207