Measuring Foster Parent Potential: Casey Foster Applicant Inventory-Worker Version (CFAI-W)
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
Objective: This article examines the psychometric properties of the Casey Foster Applicant Inventory-Worker Version (CFAI-W), a questionnaire designed to assess the potential of foster family care applicants to provide foster care. Method: Retrospective data were collected from 208 foster care workers who completed two copies of the CFAI-W, one for the best foster family and one for the worst foster family they had ever known. Results: The CFAI-W demonstrated excellent internal consistency reliability and evidence of predictive and discriminant validity. Conclusions: The CFAI-W can be used in combination with other methods to introduce standardization and accountability to the assessment of foster parent applicants.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it