Clinical challenges of adoption: Views from Montreal and Tel Aviv
Bibliographic record
Abstract
Adoption is accompanied by well-known risk factors that contribute to unique clinical challenges for children, parents, and clinicians. Adoption also serves to illustrate issues that remain relatively "silent" in the typical transition to parenthood. In this article, the authors review the normal developmental challenges that parents face during adoption, the adoption-related risk factors that may impinge on the child's development and attachment process, and the impact of adoption on the child's development of identity and filiations. We will review and illustrate clinical conditions often associated with adoption. In many countries, adoptive parents are reluctant to consult mental health clinicians during the first year of the adoption. The cases presented here illustrates the need to implement routine clinical programs for early detection and intervention of adoptive parent-infant dyads and triads at risk.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".