RISK-IN-CONTEXT: THE IMPACT OF A LOCAL LAND USE DISPUTE ON PERCEPTIONS OF TECHNOLOGICAL RISK
Bibliographic record
Abstract
This risk perception study uses a survey of households in Elgin County, Ontario and Ottawa-West, Ontario proximal to a technological hazard (land use) dispute to test the explanatory power of traditional risk perception models when applied in the local context. It is hypothesized that ‘local context variables’ - akin to the approach of the social amplification/attenuation of risk framework - will be significant predictors of perceived threat, perhaps more so than the psychometric paradigm and the cultural theory of risk. Likewise, fiduciary equity is hypothesized to be a significant predictor also. Data are analyzed using binary logistic regression and cross tabulations; most notable is the consistent significance of ‘local context variables,’ both as predictors of perceived threat from the local facility (a landfill) as well as towards non-local controversial technologies (e.g., nuclear facilities). Also intriguing is the significance of fiduciary equity specific to the local hazard as a predictor of perceived threat from non-local technologies. These findings suggest that experience with the local land use dispute is influencing (i.e., sensitizing) perceived threat from the local facility, as well as from technological hazards in general; a finding supporting the importance of specific local contexts (i.e., daily lived experience) in risk perception.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".