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Record W2097743932 · doi:10.1177/01632780122034777

Cost-Effectiveness of a Lottery for Increasing Physicians’ Responses to a Mail Survey

2001· article· en· W2097743932 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

VenueEvaluation & the Health Professions · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicSurvey Methodology and Nonresponse
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsLotteryRespondentRandomized controlled trialFamily medicineMedicineSignificant differencePsychologyStatisticsMathematicsSurgery

Abstract

fetched live from OpenAlex

To evaluate the cost-effectiveness of a lottery on physicians' responses to a mail survey, a randomized controlled trial was conducted with a random sample of 1,000 members of the Quebec Federation of General Practitioners in 1997. For the first mailing of this survey, each respondent was randomly assigned to the control or experimental group, which was offered participation in a lottery upon return of the questionnaire. Response rate was 41.2% in the experimental group and 34.8% in the control group, a 6.4% difference (CI95%: 0.6%-12.6%). The additional cost of the lottery was about Can$500, giving an incremental cost of Can$16 per questionnaire returned. In conclusion, a lottery resulted in a small but statistically significant increase in the response rate of physicians to a mail survey. This method may be a cost-effective option when applied to large surveys.

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)0.351
metaresearch head score (Gemma)0.101
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.3510.101
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.733
GPT teacher head0.633
Teacher spread0.100 · 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