National parks as cultural landscapes: indigenous peoples, conservation and tourism
Bibliographic record
Abstract
Globally. 50 per cent of all national parks and protected areas are on indigenous lands, with 85 per cent of parks in Latin America and Africa declared on indigenous territories (Kemf J 993, Amend and Amend 1995. Colchester 1996. Mackay 2002). This chapter reviews the history of indigenous exclusion and removal from national parks regarded as 'wilderness areas', starting with Yellowstone. and the relationship to tourism. By the 1980s, there was emerging recognition of national parks as cultural landscapes, inhabited by local people, with legal recognition of indigenous land rights and the advent of co-managed or jointly managed parks. Some key national parks that are now managed with indigenous groups in Australia. New Zealand, South Africa, Canada and the US are critically examined. These co-managed national parks represent the cultural identity of affiliated indigenous nations along with other political, economic and environmental values of national parks as symbolic landscapes and conservation or tourism icons representing the identity of modern nation-states. There is a focus in this chapter on governance structures allowing for indigenous inclusion in park management, cultural interpretation, cultural values and conflicts in parks and the involvement of indigenous groups in tourism and conservation within these co-managed national parks. Regaining legal control over tribal lands within parks and the reassertion of indigenous cultural identity in protected areas will increasingly define the management of conservation and tourism in these 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".