Bibliographic record
Abstract
Although climate change adaptation can occur over various political, social, and institutionalscales, the majority of adaptation decisions take place at the local level where an intimate understanding ofthe particularities of local circumstances (i.e. successful responses to past extremes events) exist alongsidea lack of formalised expertise in projecting and analyzing future possibilities. The relationship between theexperts who produce counterfactual knowledge, and the individuals who apply it, is thus central to thechallenge of responding to climate change successfully. I present a deliberately polarized caricature of thisrelationship in an attempt to facilitate knowledge exchange (i.e. to identify barriers to knowledgeexchange). Through bibliometric analysis I am able to identify various traits\characteristics of the abstractknowledge associated with the climate change adaptation literature. This “knowledge” is then placedbefore local stakeholders in a way that highlights its apparent implications for future economic, societal andenvironmental impacts, as well as its limitations and uncertainties. In this context, as derived from aphilosophy, history and sociology of knowledge perspective, a framework for discussion is initiated thatallows localised knowledge to be recognised and valued more explicitly in the planning process. Impactsin Northern Canada will be used as a case study for such analysis.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.019 | 0.018 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".