The Natural Resource Turn: Challenges for Rural Research and Policy
Bibliographic record
Abstract
Forecasts for demographic change and long-term economic growth in the world indicate a probable critical growth in demand for biological resources such as food, bioenergy, and forest products over the next few decades. In Sweden, as in other western economies where the rural economy and the rural population have been declining since the Second World War, such an expected natural resource turn may have major implications for social and economic change in rural areas. In this paper we explore the research needs that follow from the perspective of a natural resource turn, which we define as a long-term economic upgrading of natural resources following on critical growth in demand. Based on the situation in Sweden, we elaborate on four themes, considered as central to understanding natural resource turnâ€related rural change from a future perspective: (a) the production and management of biological resources and landscapes; (b) demographic change; (c) the location of economic activity to rural areas; and (d) social transformations in rural communities. Finally, some policy implications of these changes are outlined.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 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".