Transcultural Differentiation: A Model For Therapy With Ethno‐culturally Diverse Families
Bibliographic record
Abstract
This article evolved out of the writer's experience of being an immigrant, a systemic thinker, and a therapist involved in working with individuals and families from many different cultures. It proposes a model of ‘transcultural differentiation’, drawing on Western notions of separation‐individuation (Mahler) and differentiation of self (Bowen), but arguing that these concepts may have equivalents within non‐Western philosophies (e.g. Indian cultural beliefs). The model suggests that families co‐existing with both a culture of origin and an adoptive culture must inevitably change, and that in this process, they necessarily evolve into entities which transcend both culture of origin and adoptive culture. Implications for therapy are explored; in particular, it is argued that the therapist's awareness of, and sensitivity to, the transcultural experience may be more crucial than whether or not she/he shares the client's culture of origin.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.028 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".