Indigenous-Migrant Relationality in the Context of Truth and Reconciliation
Bibliographic record
Abstract
The project considers how diverse migrant communities in Canada could better address the responsibilities of truth and reconciliation with the First Nations, Inuit, and Métis and contribute to the shifting national narratives of Canada. Our overarching goal is to synthesize existing knowledge about Indigenous-Migrant relationality in the context of Canada, an emerging field of scholarship which examines the conditions that separate these two communities and elucidates potential points of connection, alliance, and solidarity. The settlement service sector, made up of community groups and organizations who support newcomer migrants upon their arrival to Canada, is our primary audience. Specific objectives include: To critically assess the state of knowledge on Indigenous-Migrant relationality in the context of Truth and Reconciliation; To identify strengths and gaps in existing scholarly, practice, and policy initiatives that bridge the divide between Indigenous and migrant communities; To provide a schema of practical, evidence-informed actions that may contribute to Truth and Reconciliation efforts by migrant communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.049 | 0.067 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".