(Re)settlement, Displacement, and Family Separation: Contributors to Health Inequality in Nunavut
Bibliographic record
Abstract
A series of relocation events in the Canadian Arctic in the mid-twentieth century contributed to widespread disruption of Inuit families. The objectives of this article are to: 1) provide a synthesis of the literature and oral histories about Inuit and Western academic perspectives on family attachments; 2) share findings from a recent study on perspectives of family relationships, which interviewed Inuit parents—many of whom were children at the time the relocation events in the 1950s and 1960s; and 3) discuss the role of severed family attachments on health inequality in Nunavut. The research was conducted within an Indigenous knowledge framework, specifically, the Piliriqatigiinniq Partnership Community Health Research Model (Healey & Tagak Sr., 2014). Data were collected in face-to-face interviews with twenty Inuit parents in three Nunavut communities. An analytical approach building on the concept of Iqqaumaqatigiinniq (all knowing coming into one), “immersion and crystallization,” was used to identify story elements in the data. Parents in the study identified the experience of forced relocation and/or attendance at residential school as traumatic events for families. These events broke the chain of Inuit knowledge transmission, which participants blamed for health inequalities observed in northern communities today. Participants who did not experience relocation attributed their confidence and ability to communicate health knowledge to the bonds they had with their children. Reclaiming and revitalizing Inuit attachment perspectives is part of the path to overcoming the trauma that Canadian Inuit families have experienced, and which is a contributor to health inequality in the region. Focusing on wellness-promoting pathways in our communities can, in turn, help reduce the health inequality gap in the North.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".