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Record W2152958049 · doi:10.1177/0899764003260961

Valuing Volunteers: An Economic Evaluation of the Net Benefits of Hospital Volunteers

2004· article· en· W2152958049 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

VenueNonprofit and Voluntary Sector Quarterly · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsYork University
Fundersnot available
KeywordsVolunteerLiberian dollarCommunity hospitalNonmarket forcesBusinessInvestment (military)Value (mathematics)Cost–benefit analysisMedicineFamily medicineNursingFinanceEconomicsPolitical science

Abstract

fetched live from OpenAlex

The use of volunteers in hospitals has been an age-old practice. This nonmarket community involvement is a distinctive aspect of North American life. Hospitals may be attracted to increase the use of volunteers, both to provide increased quality of care and to contain costs. Hospitals rely on the use of professional administrators to use the donated time of volunteers efficiently. This study examines the benefits and costs of volunteer programs and derives an estimate of the net value of volunteer programs that accrue to the hospitals and volunteers. In particular, the costs and benefits to hospitals are detailed. Using 31 hospitals in and around Toronto and surveying hospital volunteer administrators, hospital clinical staff members, and volunteers themselves, a striking pay-off for hospitals was found: an average of $6.84 in value from volunteers for every dollar spent—a return on investment of 684%. Civic and community participation is indeed valuable.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.283
Teacher spread0.257 · 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