Gaining Balance: Toward a Grounded Theory of the Decision-Making Processes of Applicants for Adoption of Children with and without Disabilities
Bibliographic record
Abstract
A grounded theory is presented of the decision-making processes among applicants when considering available children with and without disabilities for domestic public adoption. Using grounded theory methodology (Strauss & Corbin, 1998), data from 15 adoption applicants were analyzed followed the traditional three coding phases. The central category of Adoption Decision Making is labeled Gaining Balance and was the underpinning concept to all categories and sub-categories (i.e., in parentheses) of the theory: Commitment (e.g., motivation, financial considerations), Persistence (e.g., coping with emotions, counteracting pessimism), and Evaluation (e.g., assessments of personal abilities and resources, assessments of knowledge of potential adoptees' needs). The results are compared to existing literature and implications for child welfare practices and further research are discussed.
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How this classification was reachedexpand
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 | 0.004 | 0.003 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".