A political ecology of home: Attachment to nature and political subjectivity
Bibliographic record
Abstract
At the Joint Review Panel (JRP) for Enbridge’s proposed Northern Gateway pipeline across northern British Columbia, many participants presenting oral statements situated themselves as decidedly ‘ordinary’ people, with rich connections to the land and landscape. Without speaking of ownership, they nevertheless made claims to the area as their home through highly detailed articulations of knowledge and experience of its natural features. For some, it was also connected to a collective, indigenous territorial claim. In all cases, we argue that it is an articulation of ‘home,’ and that this formed the basis for the political subjectivity that led to their participation in the JRP hearings. Linking the scholarly literature on home with that of political ecology, in this paper we explore the significance of the assertion of experience and knowledge of the physical environment as the basis to claim it as ‘home’ and to assert a political right to defend it from perceived intrusion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".