Försvinner förlossningen så försvinner akutsjukvården, vem vill bo här då? : En kvalitativ fallstudie om stängningen av Lycksele BB
Bibliographic record
Abstract
In January this year, Region Västerbotten announced that the maternity ward in Lycksele would be closed until further notice. This paper is a case study of the closure of the maternity ward in Lycksele, located within the rural parts of northern Sweden. Previous research has focused on maternity ward closures in Canada and Australia whereas studies on maternity wards in northern Sweden is limited. Since large parts of northern Sweden consist of sparsely populated areas, the closure of Lycksele BB has resulted in women having to travel long distances to receive care. This paper seeks to provide a deeper understanding of the consequences of the closure of Lycksele BB by examining (1) what feelings women experience and how they manage these feelings, (2) the consequences of the maternity ward closure on women’s physical and mental health and (3) the consequences of the maternity ward closure in relation to the rural parts of northern Sweden. This study has been carried out by using a qualitative approach by conducting semi-structured interviews with two pregnant women, two mothers, and two midwives. The findings in this study show that women develop strategies to mitigate feelings of insecurity and anxiety. Both pregnant women and midwives create strategies to feel a stronger sense of control in an otherwise unpredictable situation. This contributes to major consequences for women’s mental and physical health as women are faced with new challenges, affecting their reproductive health and care. The findings also show that the closure of Lycksele BB is only a stepping stone for further welfare cuts which can result in people moving away from these sparsely populated areas. This study concludes that the issue goes beyond the closure of the maternity ward in Lycksele and raises bigger questions around the future of the rural parts of northern Sweden.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".