Some dimensions of a planning problem : residential-agricultural land use conflict in metropolitan rural-urban fringe areas
Bibliographic record
Abstract
Residential-agricultural land use conflict in the rural-urban fringe of metropolitan areas is commonly mentioned as a planning problem. The initial intent of this research was to correlate types of conflict and local planning responses in order to identify effective approaches to the management of such problems. The anticipated method would have combined theory which addresses the cause and characteristics of residential-agricultural conflict along with data from Vancouver suburbs having substantial agricultural activity and planning departments respected for their professional qualities. However, the investigation showed that the academic literature and the accessible data would not support such research. On the other hand, consultations with local planners and a review of available documentation in the municipalities of Richmond, Delta and Surrey, British Columbia, showed that residential-agricultural land use conflict is treated as a planning problem and is a source of complaints to municipal officials. Three kinds of conclusions resulted from this research. The first and second are appropriate to the underdeveloped state of the academic literature, while the first and third relate to professional practice in the absence of applicable scientific knowledge. The first is a description of the characteristics which are perceived as constituting a planning problem and a governmental response. Secondly, there are recommendations for development of data to support future research. Municipal governments in the three communities have no comprehensive monitoring system or set of cross-referenced records of complaints associated with land use conflicts. Instead, conflicts are received, identified and acted on by a variety of departments in the local government. From the descriptive material a tentative typology is offered to guide data collection and classification. Thirdly, there are suggestions which may be useful to planners who must rely on non-systematic methods to identify conflict situations appropriate for a planning response and to develop that response. The summaries of problems and responses reported are used to develop a tentative critique of present conceptualizations of appropriate planning measures. It is observed that planners have used only a few of the possible responses to rural-urban conflict. In particular, it is clear that for a wide range of conflict types there has been a reliance on land buffers to separate potentially conflicting activities. Alternative and supplementary approaches which may improve the management of typical conflict situations are suggested. These approaches focus on preventing the development of conflict through increasing the mutual understanding of the conflicting parties' points-of-view. Examples include public involvement in problem identification and resolution, as well as programs to facilitate communication between the government, farmers and non-farm residents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".