Farmland protection in British Columbia: an evaluation of the Agricultural Land Commission's application process and its impact on long-range agricultural land use planning
Bibliographic record
Abstract
There is concern that agricultural land use planning in British Columbia (BC) has become too focused upon and driven by the Agricultural Land Commission's (ALC) application process. According to Richard Bullock, former Chair of the ALC, too much prominence has been given to the application process and not enough to long-range planning. Given the importance of Bullock's statement and the potentially significant implications, it is critical to further investigate Bullock's assertions. Therefore, the purpose of this research is to analyze Bullock's statement and assess whether the ALC is driven by the application process and the extent to which it supports or undermines long-range agricultural land use planning. Data were collected through a content analysis of ALC application archives, Agricultural Advisory Council (AAC) meeting minutes for the City of Kelowna, and key informant interviews with planning professionals. Results reveal that Bullock's statement is valid, but only to a limited extent because the application process does not hinder long-range planning for farmland protection in BC the current legislative framework hinders it. The results of this study expose how the effects of a few legislative details have had the double effect of increasing the prominence of applications and constraining what long-range planning that the ALC can do. --Leaf 2.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".