Focus on Adoption: Changes, Evolution and Areas of Tension
Bibliographic record
Abstract
Research framework: Adoption has existed for many years as an institution that promotes family ties, taking forms that vary based on place, culture and time . However, the ways in which the social actors involved use adoption reveal specific conceptions of the child, the family, affiliations and family relationships. Objectives: This issue aims to identify the evolution of certain social and legislative adoption practices and to discuss the family and identity realities associated with adoption, in order to provide an analysis of how it has changed over time. Methodology: The articles in this issue highlight the many aspects of adoption: not only does it affect a number of different actors (adopters, adoptees and parents of origin), but it also raises concerns and questions of a social, legal and family nature. Results: Adoption is a subject of study at the intersection of several disciplines, including law, anthropology, sociology, psychology and social work. The various cases discussed in this issue also illustrate the importance of reflecting on the implications of adoption for individuals, families and society as a whole. Conclusions: The cases cited in these articles illustrate the need to approach adoption from a dynamic perspective that takes into account the evolution, contexts and changes involved in all the issues associated with it. Contribution: This issue is intended to stimulate reflection, both now and in the future.
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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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.015 | 0.022 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".