Bibliographic record
Abstract
Despite decades of research, few advances have been made in achieving a deeper understanding of underlying issues related to Indigenous communities in Canada who report greater health disparities than their non-Indigenous counterparts. Immersion in an Indigenous worldview is essential to developing such understanding. In this chapter, background detail is given for the qualitative analysis of an article published in the International Journal of Circumpolar Health in 2014 (“Inuit parent perspectives on sexual health communication with adolescent children in Nunavut: ‘It’s kinda hard for me to try to find the words’”). The author notes she changed to a narrative analysis after coding (in HyperRESEARCH software) started feeling disingenuous. A text-based narrative technique and crafting (several photographs of the author’s beaded amauti are provided)—both of which originate from Inuit knowledge theory such as Unikkaaqatigiinniq— were applied to understand and interpret the shared/collected stories of Inuit families about sexual health. This chapter describes how the two processes allowed for layered and meaningful interpretations of the stories, which contributed to a greater overall understanding of this health phenomena. The value of talking about one’s research with other people is also noted.
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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 | 0.015 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".