Linking Agricultural Policies with Decision-Making: A Spatial Approach
Bibliographic record
Abstract
The loss of agricultural land and its implications have been of great concern in the last decade. By undertaking a spatial analysis of the appropriation of agricultural land for urban use with an overlay of population and urban data, a focus on the consequences of certain regulations on the dynamics of land-use change is explored. This is achieved by integration of data inventories of agricultural land use for Portugal, and linking this information with CORINE Land Cover data as to assess change in the Algarve. An integrated assessment of agricultural land loss follows, undermined by the consequences of urban sprawl. In this sense, this paper expands on the currently existing decrees which provide support to sustainable development in the region while providing a qualitative assessment of future roles based on ethical values and economic efficiency and offering a feasible framework for policy-makers regarding the trends of urban/agricultural dichotomy in a planning and decision-making context.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".