Actively encouraging online responses to a mixed-mode mail and web survey: a case of nudging anglers in Ontario, Canada
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.
Bibliographic record
Abstract
Little effort has focused on encouraging less costly, online responses within mixed-mode surveys. From an Ontario angler survey, this gap is addressed by applying a nudge (i.e., mail push to web) or control (i.e., providing a print questionnaire and return envelope) for the final mail contact. The nudge increased the share of online responses from the final contact by over 40% while only slightly decreasing (1.3%) the response rate. The nudge most heavily affected senior anglers (65–70 years old) who experienced a 58% increase in online responses but an 11% decrease to the response rate from the final contact. The increased response rate for the control came at a cost of about $25 and $4 (CAD 2021) per additional response for overall and senior anglers, respectively. Thus, the cost-effectiveness of the nudge depends on the population being targeted.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it