Riskscapes: A framework for risk assessment in colonial contexts
Bibliographic record
Abstract
Risk assessment is a critical aspect of coping with environmental changes. The identification of values at risk — entities, attributes, and ideas that are important to a community — is a key component of a population's ability to resist or adapt to hazards. In colonial contexts, risk assessment must take into account the distinct relationality to the land of Indigenous and non-Indigenous groups and the historicized power relations. Most risk assessment frameworks ignore or oversimplify the cultural heterogeneity of human–environment relationships by using generalized value concepts. The few context-dependent frameworks that have been proposed do not account for different sociocultural groups living on the same land. We propose a spatial-based risk assessment approach inspired by the concept of riskscape, acknowledging diverse perceptions of risk and landscape among different sociocultural groups. We present a risk assessment method eliciting values for different sociocultural groups in their specific contexts using separate valuation methods, and then aggregating them into a joint geospatial interface to highlight convergent and competing interests. Illustrated with the boreal region of northwestern Quebec (Canada), we discuss how the riskscape framework balances Indigenous and non-Indigenous perspectives in a non-hierarchical assessment of values at risk.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".