FARMING FAMILIES AS FOSTER FAMILIES: THE FINDINGS OF AN EXPLORATORY STUDY ON CARE FARMING IN SWITZERLAND
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The terms “care farming” and “social agriculture” are used to describe the foster care that farming families provide to children, adolescents, and adults. Whereas some European countries have national systems that provide support for care farming, little is known about care farmers in Switzerland. Best estimates show that at least one percent of all agricultural family operations provide care services in Switzerland; accordingly, care farming is a component of Swiss foster care. Against the background of the recent revision of the Child and Adult Protection Act [Kindes- und Erwachsenenschutzgesetz] and of legal provisions in relation to foster care, a qualitative system analysis was carried out in three cantons in 2013. The aim of the system analysis was to describe the context and importance of care farming and to identify the attitudes and working methods of both child and adult protection authorities and family placement organizations in relation to placements in agriculture. As part of the study, documents were analyzed and expert interviews were held with representatives of both groups. The interviewed representatives of the placement authorities regard placements in agriculture as a viable option, in particular for adolescents, if the match between the client and foster family is suitable. According to the surveyed family placement organizations, the interest among farming families in offering foster places is considerable. The study presents care farming as one care service within a complex support system for children and adolescents, and raises new questions for investigation by more detailed research projects.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it