Human Perspectives and Conservation of Grizzly Bears in Banff National Park, Canada
Bibliographic record
Abstract
Some conservation initiatives provoke intense conflict among stakeholders. The need for action, the nature of the conservation measures, and the effects of these measures on human interests may be disputed. Tools are needed to depolarize such situations, foster understanding of the perspectives of people involved, and find common ground. We used Q methodology to explore stakeholders' perspectives on conservation and management of grizzly bears (Ursus arctos horribilis) in Banff National Park and the Bow River watershed of Alberta, Canada. Twenty-nine stakeholders participated in the study, including local residents, scientists, agency employees, and representatives of nongovernmental conservation organizations and other interest groups. Participants rank ordered a set of statements to express their opinions on the problems of grizzly bear management (I-IV) and a second set of statements on possible solutions to the problems (A-C). Factor analysis revealed that participants held 4 distinct views of the problems: individuals associated with factor I emphasized deficiencies in goals and plans; those associated with factor II believed that problems had been exaggerated; those associated with factor III blamed institutional flaws such as disjointed management and inadequate resources; and individuals associated with factor IV blamed politicized decision making. There were 3 distinct views about the best solutions to the problems: individuals associated with factor A called for increased conservation efforts; those associated with factor B wanted reforms in decision-making processes; and individuals associated with factor C supported active landscape management. We connected people's definitions of the problem with their preferred solutions to form 5 overall problem narratives espoused by groups in the study: the problem is deficient goals and plans, the solution is to prioritize conservation efforts (planning-oriented conservation advocates); the problem is flawed institutions, the solution is to prioritize conservation efforts (institutionally-oriented conservation advocates); the problems have been exaggerated, but there is a need to improve decision-making processes (optimistic decision-process reformers); the problems have been exaggerated, but managers should more actively manage the landscape (optimistic landscape managers); and the problem is politicized decision making, solutions vary (democratizers). Although these 5 groups differed on many issues, they agreed that the population of grizzly bears is vulnerable to extirpation, human use of the area should be designed around ecological constraints, and more inclusive decision-making processes are needed. We used our results to inform a series of workshops in which stakeholders developed and agreed on new management strategies that were implemented by Parks Canada. Our research demonstrates the usefulness of Q method to illuminate people's perspectives and identify common ground in settings where conservation is contested.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".