Home-Based Family Therapy: A Misunderstanding of the Role and a New Challenge for Therapists
Bibliographic record
Abstract
The family therapy field has hesitantly incorporated the home-based family therapy modality. Today, there are a number of agencies offering home-based family therapy in response to the increasing need to reach out to multifaceted problem families and to ensure the continuity and effectiveness of treatments. Nonetheless, there is little research and literature supporting this approach, and no clear guidelines for home-based therapy practice have been developed to date. Many academic institutes fail to train therapists in this area, despite the fact that it is a growing market trend. This article examines the literature describing home-based therapy, provides an analysis of its weaknesses and strengths, and formulates some considerations for therapists interested in its practice.
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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 | 0.025 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.054 |
| Scholarly communication | 0.008 | 0.020 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.009 | 0.020 |
| 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 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".