Are we being served? A critical perspective on Canada’s Citizens First satisfaction surveys
Bibliographic record
Abstract
Background: Citizen satisfaction surveys are used in many jurisdictions to measure attitudes towards public services and inform service delivery improvement strategies. Canada is regarded as a world leader in the field due to its internationally influential Citizens First surveys. Aim: This study aims to determine the soundness of the design, execution and reporting of Canada’s Citizens First surveys. Method: It presents a critical methodological review drawing on several social scientific paradigms including survey research, interpretivism and post-structuralism. Results: The Citizens First surveys contain significant problems in terms of sample representativeness, validity of causal claims and treatment of subjective opinions. These surveys can also be criticized for the influence they have had on the direction of public service reforms. Survey findings have been invoked to support the shift to private sector models of delivery and encourage a narrow and passive view of the role of the citizen in official decision-making. These developments conflict with other realities and values in contemporary administration and governance. Conclusion: Canada’s citizen satisfaction surveys contain important methodological weaknesses which must be acknowledged and rectified if reformers wish to extend the scope and effectiveness of current service delivery innovations. Points for practitioners Canada’s citizen satisfaction surveys are widely regarded as models for other jurisdictions to follow, yet they have significant limitations, including very low response rates, which mean the findings are not representative of the population’s views on government service delivery. Although the surveys claim to identify the specific elements of service delivery that cause increases in general citizen satisfaction with the performance of governments, the existing methodology does not permit such assertions. These surveys present a private-sector-inspired view of the service user as a customer, and suggest that all users of government services value the same things. This view fails to capture the diversity of government service delivery and is particularly inappropriate in complex policy areas such as human and social services.
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How this classification was reachedexpand
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 | 0.003 | 0.013 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".