Working Together with South Saami Birth Stories – A Collaboration Between a Saami Midwife and a Saami Researcher
Bibliographic record
Abstract
This paper presents some results from a community-based project among local South Saami in the Norwegian and Swedish part of Saepmie. I was co-coordinating a two-year community-sponsored project in the community (Røyrvik) in which a local South Saami midwife documented stories from elder Saami about childbirth in earlier times, both from their own memories and from stories they knew. Her work became an article in a book, and the project helped us to understand much more about childbirth and general living conditions for Saami one to three generations ago in this area. As a PhD candidate, I have complemented her work with a theoretical framework (Indigenous Research Methods, colonial perspective), a historical analysis, and a contemporary context. Apart from presenting an example of stories she was given and how they can give us new knowledge. But I will focus on the meanings, processes, theories and practices of engaged Indigenous community research. I will describe our different methods and the benefit of working together and will point out how it will further research.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.044 | 0.018 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".