Bibliographic record
Abstract
The purpose of this study was to examine how Sweden organizes their adoption education program since it differs from adoption agencies in Canada. The aim was to find out why Sweden has a different organizational strategy compared to an adoption agency in British Columbia in Canada when the content in the adoption education program basically is the same in both countries. It was of interest to examine how supervisory authorities in Sweden deal with issues regarding the quality within the area of adoption. Six interviews were made in Sweden with participants from different organizations that carry out adoption related work. During the interviews the participants were asked questions about the history of the education program, how it’s organized, its purpose, adoptions agencies involvement in the program, and whether the program is considered to reach its purpose. An interview was made over the Internet with two social workers at an agency in British Columbia and they were asked similar questions about their program. I used a theory by Lee G. Bolman and Terrence E. Deal to identify, analyze and offer an explanation to the organizational strategies in both Sweden and Canada. I found that municipalities in Sweden are giving the responsibility for the provision of adoption education programs to clients without any involvement from the adoption agencies. Agencies in Sweden are considered not to be involved as they could affect the objectivity for the clients to reach an independent decision whether to proceed with their adoption plans. In Canada however the adoption agencies are considered it to be an advantage for them to have responsibility of the program as it gives them an opportunity to educate their clients on adoption related issues. Supervisory authorities in Sweden reports how the quality of their adoption education program can vary among municipalities throughout the country. Key words: adoption education program, quality, roles, integrated, separated.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".