The Intricacy of Policy Making: Assessing Environmental Management in the Lower Athabasca, Alberta, Canada
Bibliographic record
Abstract
This thesis explores societal–environment interactions in the context of environmental policy making processes in the Lower Athabasca, Alberta, Canada. Applying insights from the Actor-Network Theory, the thesis systematically analyses the policy making network by identifying and explaining embedded network processes. Particularly the thesis shows how different discursive and practical techniques are used by actors to characterise other entities, and configure the relationship between human development and the natural environment. The thesis demonstrates how the culture–nature dichotomy constructed in environmental management is problematic for environmental policy making processes. Environmental management entails the negotiation and settlement of deep differences regarding cross-cultural understandings of human society’s position within the environment. The dichotomy has a profound impact on power dynamics in the network and even triggers a reversion of the network forming process to the framing of environmental issues. As such the thesis concludes that network formation is not a linear process but that networks have an emergent quality. Elaborating on new ecological thought in ecological anthropology, the thesis further explains that societal–environment interactions do not only occur in the physical environment, but also in policy making processes.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".