Family Assessment Measure (FAM) and Process Model of Family Functioning
Bibliographic record
Abstract
This paper provides an overview of twenty years' work in the development of the Family Assessment Measure (FAM), based on the Process Model of Family Functioning. The Process Model describes a conceptual framework for conducting family assessments according to seven key dimensions: task accomplishment, role performance, communication, affective expression, involvement, control, values and norms. The FAM provides measures of these dimensions at three levels: whole family system (general scale, fifty items), various dyadic relationships (dyadic scale, forty‐two items) and individual functioning (self‐rating scale, forty‐two items). In addition, the general scale includes social desirability and defensiveness response style measures. Brief FAMs (fourteen items) are available for each scale as well. The measurement properties of FAM have been evaluated in a variety of clinical and non‐clinical settings. Reliability estimates are very good in most contexts. FAM's validity has been supported using a number of techniques. Overall, the weight of the evidence is that FAM's effectively and efficiently assess family functioning and provide strong explanatory and predictive utility. This empirical evidence reinforces experiences of clinicians, indicating that FAM provides a rich source of information on family functioning.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".