Situated engagement: a critique of wildlife management and post-colonial discourse
Bibliographic record
Abstract
A review of the literature informed by fieldwork in Australia, Canada, Zimbabwe, Namibia and South Africa is used as the basis of a critique of wildlife management and post-colonial discourse. It is argued that many of the concepts and practices that dominate wildlife management are firmly embedded in Eurocentric epistemologies that are falsely assumed to be universally applicable. This assumption justifies imposition of concepts and practices such as wildlife, management, conservation, development, co-management, community-based natural resource management and traditional ecological knowledge. Although this informs what is seen as a well-intentioned post-colonial discourse, it in fact masks the reimposition of colonising relationships. Critical discussion of what is meant by 'wildlife' and 'management' identifies the beliefs that underlie the concepts and practices of wildlife management and the way they are internally related to colonising processes. Wildlife management, therefore, is constantly at risk of reinforcing colonising relationships, and limiting imaginaries and realities by straight-jacketing thought and action within a 'hall of mirrors' - within the boundaries set by the Eurocentric belief that things are binarised as either society or nature, human or animal, wild or tame/domestic, and must be either conserved or developed through management. Throughout the thesis, glimpses into multiple knowledges, and experiences of resisting and being, are drawn from fieldwork and literature sources. These glimpses unsettle and challenge the assumed universality of dominant wildlife management approaches, and show that Eurocentric beliefs and practices are neither universal nor all-powerful. Situated engagement is introduced as an approach that addresses both the concepts and practices of wildlife management and the multiple worlds that wildlife management silences, ignores, devalues and undermines. Situated engagement is not a new management framework, but offers an approach to guide interactions in specific material, conceptual and discursive places. Ultimately, the thesis argues that engaging in these situated places meets the challenges of contemporary circumstances by recognising, imagining and realising possibilities that are unimaginable within the hall of mirrors.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.028 | 0.162 |
| Scholarly communication | 0.021 | 0.019 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.008 | 0.009 |
| 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".