Bibliographic record
Abstract
This chapter reviews qualitative research on the scarcity of renewable resources and violent conflict from the 1990s and crucial debates among scholars about the findings of two key research projects in Canada and Swizerland. These research projects link human-induced scarcities of renewable resources to violent conflict indirectly, through secondary impacts such as economic and livelihood impacts, reduced state capacity, and dislocation and immiseration caused by the seizure of valuable but scarce resources. Research in the past decade on possible linkages between climate change and violent conflict have drawn on the findings from research in the 1990s to suggest how climate change can contribute to violent conflict – rarely if ever as a sole causal factor, but instead acting to worsen and aggravate existing impacts and cleavages in societies. Controversies that raged over the findings of the 1990s research around the definition of the independent variable, the causal strength of political versus environmental factors, and the debates over greed or grievance as causes of violent resource conflict remain unsettled. Some of these debates, such as the causal role of political and environmental factors have resurfaced in similar form in recent debates about the links between climate change and violent conflict.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".