Outdoor recreation planning in Alberta : appraisal of an information generation process
Bibliographic record
Abstract
It is becoming apparent that some issues in natural resource management do not lend themselves to the technical, 'value-neutral' approach to decision-making that has often characterized this function of government. One of these issues is outdoor recreation, which has become a resource use equally important to such traditional uses as water management, mineral extraction, and forest harvesting. Choices made with respect to recreational use of natural resources inevitably reflect the perceptions and priorities of those individuals who participate in making the choices. Resource managers who make decisions about the use of natural resources in the 'public interest’ must seek to optimize, that is, to choose that alternative course of action which yields the greatest net benefits to society. This study purports to assess how well the Provincial Parks agency of the Province of Alberta generates information which can lead to optimal decisions in recreation resource management. A discussion of the growing importance of outdoor recreational use of resources, and of the public nature of outdoor recreation opportunities provided by government agencies, precedes a brief analysis of a number of decision models. The latter analysis suggests that the generation of information about alternative choices is an important determinant of the outcome of the decision-making process. Accordingly, a number of criteria are proposed which will permit an evaluation of the provincial parks agency's approach to providing information for decisions regarding the management of outdoor recreation resources in the province. The provincial parks agency is described in terms of its administrative environment, its evolution since 1952, and the operation of the information generation process in the agency. Contextual information on the attitudes of provincial residents towards outdoor recreation is drawn from a survey of outdoor recreation behavior and perceptions carried out in the Peace River region of Alberta in 1972. The study concludes with the evaluation of the agency's operation in terms of the criteria proposed earlier in the study. For those aspects of information generation in which the criteria are not met, suggestions for improvement are offered. These include the definition, through public discussion, of the agency's role in providing a range of outdoor recreational opportunities for residents of, and visitors to, the province. Secondly, it is suggested that the scope of the agency's planning process should be expanded so that the provision of outdoor recreational opportunities can be considered a problem of supply as well as demand; information about the benefits and costs of alternative uses of recreational resources, and the benefits and costs of using resources that are suitable for recreation for other purposes, would be generated if such an approach was adopted. Finally, it is suggested that, in order to adequately reflect the full range of societal values in its decision process, the agency should institute a program of consultation with the public, whereby citizens would participate in decisions regarding such matters as general policy direction and major parks projects. The attachment of a permanent public advisory committee to the office of the Minister responsible for provincial parks is suggested as a medium through which Albertans may participate in planning their provincial parks.
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".