Response Bias in Voluntary Surveys: An Empirical Analysis of the Canadian Census
Bibliographic record
Abstract
In 2011, the National Household Survey replaced the traditional Long Form Census in Canada. The questions in the National Household Survey were similar to the Long Form Census, but responding to this survey was no longer mandatory. This paper provides an empirical analysis of the information loss arising from the change to a voluntary response policy. Comparisons of the differences between the non-mandatory 2011 National Household Survey and the 1996, 2001, and 2006 mandatory Long Form Census are used to identify changes related to the response policy. Using two-sample Kolgomov-Smirnov tests, differences in income distributions are tested to find that high income earners are underrepresented in the voluntary survey. This finding is corroborated by comparisons of various inequality measures across these time periods. Differences in discrete variables are tested using differences in proportions and Pearsons chi-squared tests. Systematic misrepresentation of certain groups is found in the voluntary survey. The switch to a voluntary response policy in 2011 likely led to an over representation of women and married individuals.
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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 | 0.084 | 0.340 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.024 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".