The Downward Trend of Survey Response Rates: Implications and Considerations for Evaluators
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
Abstract: Rapidly declining response rates and the associated threat of nonresponse bias call into question the validity of data obtained through telephone surveys, a tool often used in evaluation. This article explores changes in nonresponse bias over time by examining three data points (1991, 1996, and 2002) from an annual household telephone survey conducted by the University of Alberta’s Population Research Lab. Results demonstrate a substantial decline in response rates accompanied by an increasing level of bias in variables related to respondent education. Implications of these results are investigated through regression analyses and suggest that declining representation of individuals with less education could significantly impact a variety of survey variables, thus creating opportunity for opinions of the more educated to become more heavily weighted in evaluation results. In turn, such results could be used to inform government policies and programs in ways that advantage the educated middle class.
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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 | 0.150 | 0.137 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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