Prepaid Monetary Incentives—Predictors of Taking the Money and Completing the Survey
Bibliographic record
Abstract
Prepaid monetary incentives are used to address declining response rates in random-digit-dial surveys. There is concern among researchers that some respondents will accept the prepayment but not complete the survey. There is little research to understand check cashing and survey completing behaviors among respondents who receive pre-payment. Data from the International Tobacco Control Four Country Study-a longitudinal survey of smokers in Canada, the US, the UK, and Australia, were used to examine the impact of prepayment (in the form of checks, approximately $10USD) on sample profile. Approximately 14% of respondents cashed their check, but did not complete the survey, while about 14% did not cash their checks, but completed the survey. Younger adults (Canada, US), those of minority status (US), and those who had been in the survey for only two waves or less (Canada, US) were more likely to cash their checks and not complete the survey.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".