The Best Interests of the Child?: The Cultural Defense As Justification for Child Abuse
Bibliographic record
Abstract
As the world continues to shrink and immigration increases across the globe, children are more frequently being raised under the influence of several cultures. As these cultures clash, children may be subject to child-rearing practices that are abusive in one culture and accepted in another, leaving state criminal court systems to sort out the aftermath. In these cases, the accused immigrant parents may be able to use the cultural defense to escape conviction or mitigate their sentences in the face of child abuse charges. This cultural defense has been successfully used in courts all over the world, including the United States, the United Kingdom, Canada, and many other countries. The tremendous and increasing mobility of the global population will likely magnify the conflicts of the past and increase the use of the cultural defense in child abuse cases in the future. Part I of this article discusses the trends in immigration and parenting that make use of the cultural defense increasingly more likely in the future. It also explains the cultural defense and children's rights under the CRC. Part II discusses the best interests principle of the CRC as the framework from which to analyze the use of the cultural defense in child abuse cases. Then, in Part III, this article analyzes the use of the cultural defense in child abuse cases from around the world under the framework of the CRC and explains why its use is in direct conflict with the CRC. Finally, Part IV proposes an internationally-derived standard against which judges or juries should compare the acts of immigrant parents in child abuse cases.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.027 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 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".