Bibliographic record
Abstract
This thesis traces how Secwépemc people conceptualize and (re)imagine their relationships with water across the Secwépemc nation. Using a mixed method of qualitative knowledge through one-on-one interviews with relatives and Secwépemc community members I use a strength-based research approach that honours and upholds Secwépemc voices. I include Secwépemc voices of Elders, educators, and youth to share stories and visions of Secwépemc water governance across five Secwépemc communities (Cstélen, Neskonlith, Tk’emlúps, Simpcw, and Sexqeltqín). The Secwépemc value of k'wseltktnéws is used as a theoretical and methodological approach to explore Secwépemc water knowledge and relationality. I examine how settler-colonialism and capitalism impact and attempt to disrupt Secwépemc people and communities’ embodiment, care, and responsibilities to water. Additionally, I discuss how resource extraction practices and narratives shape Secwépemc water governance. This thesis enables Secwépemc people and communities to (re)imagine water governance through the value of k'wseltktnéws, Indigenous futurity, Indigenous feminism, and grounded normativity. This thesis opens up space to improve upon Secwépemc relationality to each other and to water so that our tellqelmucw, the people to come, are supported and able to live freely within Secwepemcul’ecw (Secwépemc land and waterways).
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.038 |
| Scholarly communication | 0.007 | 0.017 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".