Dealing with Ambiguity: On the Interdependence of Change in Agriculture and Rural Communities
Bibliographic record
Abstract
ABSTRACT The well‐established linkages between the fortunes of agriculture and rural communities that have characterised the histories of rural areas in New Zealand and elsewhere have been severely challenged over the past two decades. Some commentators have posited a de‐coupling of the two sectors. This paper explores evolving farm and rural community interactions in New Zealand, first with reference to a descriptive model and second with reference to the lived experiences of rural residents in two Central North Island communities, Taumarunui and Tirau. The key finding from the research is that the distinction between de‐coupling and re‐linking while conceptually appealing is empirically problematic as observed trends suggest a complex and ambiguous mixture of both.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.062 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".