New Discourses on Energy Transition as an Opportunity for Reconciliation? Analyzing Indigenous and Non-Indigenous Communications in Media and Policy Documents
Bibliographic record
Abstract
This article examines energy issues articulated by Indigenous and non-Indigenous people in Canada and analyzes the energy transition as a locus of reconciliation therein. Using content and discourse analysis of policy documents, white papers, and news media articles, we draw attention to reconciliation and energy discourses before and after 2015, the year that marked the release of the Truth and Reconciliation Commission of Canada (TRC) report and the Paris Agreement on climate change. We find a three-fold expansion of those discourses, which encompass issues of inclusion and exclusion, dependency, and autonomy, as well as colonial representations of Indigenous people, after 2015. We also find that non-Indigenous voices are more prominent in those conversations. We suggest that the prospects of mutual benefits could turn the energy transition into an opportunity to bring together Indigenous and non-Indigenous people in Canada.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.018 | 0.034 |
| Scholarly communication | 0.020 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".