Multifunctionality of farmland and farm activities & multi-actor involvement in agricultural development planning
Bibliographic record
Abstract
This article deals with the conservation of farmland and its farm activities, and the role of their multi-functionality in increasing the potential for conserving good quality farmland and its farm activities. This is especially important given the fact that traditional land use planning has frequently not been able to conserve good quality farmland and large areas of such farmland have often been removed by governments and their planners to support the development of subdivisions and industrial parks. There have however been some substantial improvements in some jurisdictions such as in two of the provinces of Canada, viz. British Columbia and Québec. But even with special legislation to conserve good quality farmland, some land was still removed. Hence, as a very novel move at the end of the 1990s, the province of Québec suggested to its Regional Municipal Counties to support the development of a strategic development plan for agriculture for their agricultural reserves and to involve different actors who supported the conservation of good quality farmland and its farm activities because of one or more of the multiple functions that farmland can support. Successful efforts led to the involvement of multiple actors who supported the conservation of good quality agricultural land because such land also frequently supported multiple other functions of value to society. As an example, the municipality of Senneville at the western end of the Island of Montréal demonstrates this multi-functionality and the involvement of several of its farmers in undertaking actions, including in an Action Research process, to support the multiple other functions of their farmland and its activities which they communicated to their municipality and to other organizations which were also interested in conserving good quality farmland and its farm activities.
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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 | 0.004 | 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 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".