Unveiling the Paradox: Reconciliation Paths in Sweden and Canada.
Bibliographic record
Abstract
Sweden and Canada are internationally recognised for their contributions to defending human rights and managed to establish a reputation as humanitarian superpowers. However, both countries deal with the aftermath of a long violent past, concerning the dreadful treatment of their respective indigenous populations. In two separate contexts, the First Nations, Métis and Inuit peoples in Canada and the Sámi population in Sweden have been subject to strict assimilation policies, violations and other expressions of oppression across decades, but now, things are about to change. The purpose of the thesis has been to examine the current processes of reconciliation in the two countries by analysing the presence of the indigenous minorities’ narratives in the reconciling work. Auerbach’s Reconciliation Pyramid has served as the theoretical framework for the analysis, consisting of seven stages working with reconciliation: acquaintance, acknowledgement, empathy, responsibility, restitution, apology and narrative incorporation. The findings of the comparative study are that narratives play an important role in reconciliation processes, as conflicts involving indigenous peoples have to concern both identity and territorial matters. The study indicates that Sweden has not integrated the narratives of its indigenous population to the same extent as Canada, which explains why the Swedish reconciliation process has not progressed further.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.057 | 0.025 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| 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".