Impact of Child Maltreatment on Attachment and Social Rank Systems
Bibliographic record
Abstract
Child maltreatment is a prevalent societal problem that has been linked to a wide range of social, psychological, and emotional difficulties. Maltreatment impacts on two putative evolved psychobiological systems in particular, the attachment system and the social rank system. The maltreatment may disrupt the child's ability to form trusting and reassuring relationships and also creates a power imbalance where the child may feel powerless and ashamed. The aim of the current article is to outline an evolutionary theory for understanding the impact of child maltreatment, focusing on the interaction between the attachment and the social rank system. We provide a narrative review of the relevant literature relating to child maltreatment and these two theories. This research highlights how, in instances of maltreatment, these ordinarily adaptive systems may become maladaptive and contribute to psychopathology. We identify a number of novel hypotheses that can be drawn from this theory, providing a guide for future research. We finally explore how this theory provides a guide for the treatment of victims of child maltreatment. In conclusion, the integrated theory provides a framework for understanding and predicting the consequences of maltreatment, but further research is required to test several hypotheses made by this theory.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".