From blank spaces to flows of life: transforming community engagement in environmental decision-making and its implications for localism
Bibliographic record
Abstract
Localism advocates the participation of ‘local’ groups in governmental decision-making processes. While making policy more context/place specific is a progressive goal, this paper suggests that the processes through which this occurs, and underlying conceptual approaches to scale and place, require a careful analysis. Although often side-lined, Indigenous experiences of localism are key to seeing these issues as critical responses to place and politics, rather than relegating them to an ‘Aboriginal’-specific issue. This paper outlines two practical implementations of Aboriginal inclusion in environmental decision-making, in Canada and Australia. These case studies demonstrate both the failings of current framings of localism and ‘environment’ in policy-making and the inadequate responses of governments to the complexities of place making. These challenges are illustrative and symptomatic of wider issues about how environmental policy and place are currently envisaged. This paper suggests a new methodological framing of these issues that positions the current framing as one view among many, offers a non-relativist frame of communication for moving beyond inclusion and outlines the implications of this reframing for localism.
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.
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 | 0.027 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.134 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".