Conserving Common Ground: Exploring the Place of Cultural Heritage in Protected Area Management
Bibliographic record
Abstract
That parks and protected areas are places where the conservation of cultural heritage can and should take place has not always been immediately apparent. However, today there is widespread acknowledgement that the management of cultural heritage resources needs to be brought into large-scale planning and management processes in an integrated and holistic manner. This is particularly true in protected areas, which not only contain significant cultural heritage resources, but are also often mandated to conserve these resources and can benefit significantly from the effort. This dissertation aims to address the challenge of integrating cultural heritage conservation into protected area management. Focusing specifically on Alberta, this research employs a qualitative methodology to undertake a broad document analysis and a series of in-depth qualitative interviews with protected area managers to identify the current state of cultural heritage conservation in the provincial protected area system, as well as the strengths, weaknesses, and opportunities that exist. Using this information, a set of policy recommendations are developed. Ranging from high-level policy goals to site-specific tools and resources, these recommendations aim to support more effective cultural heritage conservation in Alberta.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.027 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".