A Better Adoption? Evolution, Challenges, and Projections of Chilean Adoption Policies and Practices
Bibliographic record
Abstract
Abstract Following a regrettable history of forced adoptions, Chile underwent a pivotal shift in its adoption policies and practices with the ratification of the UN Convention on the Rights of the Child (1989), the Hague Adoption Convention (1993), and the enactment of Law 19.620 (1999). In the last decade, the country has embarked on an unprecedented reform of its child protection system. Aligned with global trends, Chile has also seen a rise in contested adoptions from care. These ongoing transformations present both significant challenges and critical opportunities to reorient child protection and adoption policies. This article examines the evolution, current dynamics, and future prospects of the Chilean adoption system across cultural, legal, institutional, and practical dimensions. We analyze the implications of these changes for adoption policies and practices, highlighting the urgent need for a child-centered approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".