Cumulative effects, anthropogenic changes, and modern life paths in sub-Arctic contexts. Envisioning the future in Northeastern British Columbia: the case of the Doig and Blueberry River First Nations
Bibliographic record
Abstract
This work is an attempt to describe what is happening in North-eastern British Columbia, in an area where extractivism intertwined with the market-driven economy had been generating changes not always foreseen, understood, and mitigated. Drawing on my year of fieldwork (July 2019 - August 2020), I explore how the traditional lifestyle and socio-economic organization of the Doig and Blueberry River First Nations have been changed by the cumulative effects of industrial development. At first glance, resource extraction may be perceived as a solution to tackle the many problems of scattered and isolated Indigenous communities (i.e. unemployment, lack of opportunities for socio-cultural and economic continuity in the area). However, enjoying the benefits extractivism produces comes at a high price. It impacts Indigenous cosmovision and cultural heritage while shaping how community members envision the future and the kind of future(s) they perceive as possible. \nThe timeliness of this ethnographic work is also confirmed by the litigation BRFN v. BC (2015-2021). For the first time in Canadian legal history, a trial on cumulative effects intertwined with Treaty 8 infringements and the recognition of Constitutional rights was initiated by a First Nation Band in an attempt to stop development projects to which the Band did not give its consent. The litigation came to an end in June 2021, with a ground-breaking verdict in which it was judged that the BC province could not continue to authorize activities that breach Treaty 8 and its unwritten promises. As a result, on 7th October 2021, a preliminary agreement between BRFN and the BC Government was reached. The province has agreed to allocate a total amount of C$ 65 million to the BRFN for land restoration activities and cultural practices revitalization. \nTo explain the complex reality community members (and Fort St. John residents) meet in their everyday lives while facing extractivism, I introduce the concept of ‘atemporal modernity’ as an (a)temporal status in continuous becoming. I argue that people are trapped in such a status, perpetually waiting for a better future yet to come, which can only be achieved through extractivism. By letting people talk, I try to describe their everyday challenges while exploring which kind of future(s) community members envision to keep living off the land as long as ‘the sun shines, the rivers flow, and the grass grows’.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".