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Record W2077841078 · doi:10.1080/03637751.2010.495948

The Effectiveness of High- and Low-Intensity Worksite Campaigns to Promote Organ Donation: The Workplace Partnership for Life

2010· article· en· W2077841078 on OpenAlexaff
Susan E. Morgan, Tyler R. Harrison, Lisa V. Chewning, Mark J. DiCorcia, LaShara A. Davis

Bibliographic record

VenueCommunication Monographs · 2010
Typearticle
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsPurdue Pharma (Canada)
Fundersnot available
KeywordsInterpersonal communicationGeneral partnershipControl (management)Organ donationPsychologyDonationMedicineAdvertisingEnvironmental healthSocial psychologyBusinessPolitical scienceSurgeryTransplantationManagement

Abstract

fetched live from OpenAlex

This study describes a worksite project designed to promote organ donation while testing the effectiveness of low-intensity (media-only) campaigns compared to high intensity campaigns (media+interpersonal communication), which incorporated on-site visits. All campaigns lasted 10 weeks. A total of 45 companies participated in the project, 15 in each quasi-experimental condition. Companies were counterbalanced by size of organization and industry type. Compared to the control condition, high-intensity worksite campaigns led to a six-percentage point increase in signed donor registrations while low-intensity campaigns led to a three-percentage-point increase. Both forms of worksite campaigns led to increases in attitudes, knowledge and perceived subjective norms from pretest to posttest when compared to control sites. At the same time, worksite campaigns served to significantly reduce individual-level barriers shown to be related to donation, such as medical mistrust and desire to maintain bodily integrity.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.000
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 head0.019
GPT teacher head0.306
Teacher spread0.287 · 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

Citations31
Published2010
Admission routes1
Has abstractyes

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