Local Development and Sustainable Periurban Agriculture: New Models and Approaches for Agricultural Land Conservation
Bibliographic record
Abstract
Periurban agricultural territories have had to confront many pressures over the last 70 years, ranging from land development pressures emanating from nearby large cities and metropolis to technological change, to the draw of the urban labour market on farmers' families, to the consequences of climate change and variability. They are also increasingly expected to provide stable supplies of foodstuffs to the nearby urban markets as well as having the potential to respond to many other urban demands for other functions that these agricultural areas can support. Periurban agricultural areas can be considered as strategic components of urban and metropolitan regions. They have much more to offer to their regional economies and societies than simply food production because they are also support multiple functions, both market-based and non market function. Market-based functions include the production of foodstuffs for the urban market as well as functions related to both tourism and leisure activity. Non-market based functions include the conservation of landscape heritage, and water and biodiversity conservation; some of these can also be transformed into functions that generate supplementary income for the farming families. Some functions serve to strengthen the linkages between farming, farm families and nearby urban areas. For this strengthening to occur, it appears essential that: a) farmers and their families become involved in the development of their own multifunctional agriculture-based projects; and b) the significance of the non-agricultural functions must also be appropriated by non-agricultural actors, such as local government, nearby city governments, community and consumer organisations. These points are illustrated by examples drawn from several countries, including research-action projects involving the two authors neat Montréal. These latter projects, appropriated by the local farming communities, involve local development processes that can be modified to deal with periurban agricultural areas in any political and cultural context. These processes involve the development of new models of agricultural development and relatively new approaches to local and community development. These processes reinforce regional and national programs of agricultural land ‘protection' which, it is argued, need such supportive local and community development processes in order to be effective.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".