Influence of a private–public risk pool and an opt‐out framing on earthquake protection demand for Canadian homeowners in Quebec and British Columbia
Bibliographic record
Abstract
This article describes the design and analysis of web-based choice experiments that examine how the demand for earthquake protection in Quebec and British Columbia (BC), Canada, is influenced by the default option and the structure of the insurance plan. Homeowners in both provinces were given the opportunity to purchase protection against earthquake losses when presented with one of the following options: the current private insurance plan and proposed public-private Risk Pools with different levels of the public layer. The default frame was changed so the homeowner could either opt-in by purchasing this coverage or opt-out of being given this protection and receiving a premium discount. Assigning participants to the public-private Risk Pools rather than the current private insurance plan increases the likelihood of purchasing earthquake insurance protection by an odds ratio of 2.7 or greater in BC and Quebec. Furthermore, opt-out enrollment design substantially increases take-up of earthquake protection relative to opt-in enrollment. The policy implications of these findings are discussed.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".