Environmental History and the Concept of Agency: Improving Understanding of Local Conditions and Adaptations to Climate Change in Seven Coastal Communities
Bibliographic record
Abstract
Abstract This article provides a synthesis of the results from seven global research sites working together to study adaptation to climate change in coastal communities under the moniker ARTISTICC (www.artisticc.net). It first aims to share these research results in order to demonstrate two general themes that emerge from our analysis and can help improve our understanding of community responses to environmental change broadly speaking. These themes are the continuity of environmental change and the legacy of colonialism. The goal is to demonstrate that comparisons across research sites are possible if an appropriate transdisciplinary framework is in place and also that environmental history is required to understand the past if we are to effectively tackle present conditions. Secondly, this paper offers reflections on the concepts of agency and adaptation and how the methodological divide between historians and social scientists can be further bridged to great benefit for all concerned. By being more reflective on our own disciplinary cultures, we can co-construct knowledge about how community cultures operate. The agency of local actors is central to understanding past choices and present obstacles to successful adaptation. Indeed, we must better appreciate the goals of local actors if we are to know what success looks like to them. Adaptation, whether adjustment or transformation, is often a long-term, complex process.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".