The Effect Of Interviewer Attitude on Survey Cooperation
Bibliographic record
Abstract
Research to improve the quality of social surveys has shown that methodological factors have a significant impact on respondent cooperation. The research presented here is inspired by the sociology of work and studies the impact of interviewers' sense of motivation and “self-efficacy” in convincing respondents to answer surveys. To do so, a survey of interviewers working for three private pollsters was conducted during the Canadian federal election campaign of November 2000. The results indicate some evidence of relationships between motivation, sense of self-efficacy (and associated behaviour), and interviewer performance. However, some of the results could be better explained by differences in training. In addition, the lack of a better measure of performance may also explain the weakness of the results. Future studies should examine performance measurement and try take into account how performance changes over time. Surveys, Interviewers, Interviewer Performance, Interviewer Attitudes, Measurement of Interviewer Performance.
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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 | 0.486 | 0.676 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".