Direction for interpretive programming from Alberta Provincial Park management plans
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Park management plans provide strategic direction for the future management of specific parks. These plans set goals and strategies for many park management concerns, including ecological integrity, visitor services, facilities, boundaries, and resource allocation. Understanding interpretive goals, topics, and strategies will help a park or park system develop a coherent approach to interpretive planning, delivery, and evaluation. This study determined how interpretation was prioritized in Alberta provincial parks’ management plans. We analyzed 32 management plans based on length (average of 80 pages), age (average of 14 years), goals, topics, and strategies. Overall, 84% of the plans addressed interpretation, devoting an average of 3% of their length to interpretation. The most targeted interpretive goals were “learning,” “increasing positive attitudes,” “behavior change,” and “enjoyment.” The most frequent interpretive topics were “heritage,” “culture,” “conservation,” and “flora or fauna.” The most common interpretive strategies were “signs,” “general personal interpretation,” and “guided hikes.” Even though interpretation received a low emphasis, newer plans provided more emphasis, expanding on conceptualizing and evaluating interpretation compared with older plans. By summarizing the priorities of management plans for interpretation, this study may help park staff set interpretive goals, evaluate progress, and promote consistency between the goals of park staff and outcomes for visitors. In turn, this information may help park planners and practitioners to better align interpretive goals, strategies, and outcomes.
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.
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) | 0.000 | 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 it