Why Some Children Come to School with “Baggage”: The Effects of Trauma Due to Poverty, Attachment Disruption and Disconnection on Social Skills and Relationships
Bibliographic record
Abstract
Children living in adverse conditions of poverty and/or abuse or in institutional or foster care, suffer physiological changes in their developing brains which negatively affect their social skills and therefore their ability to socialize and form meaningful connections with others. Impeded social skills development also interferes with children’s ability to demonstrate self-control, to learn and to demonstrate appropriate behaviour. Their physical and emotional health and wellbeing also suffer. Without greater understanding, intervention and support from schools, the future for these children continues to look extremely bleak. The emotional and social costs are high. This paper looks at the effects of trauma due to poverty, parent-child separation (attachment disruption) and disconnection on social skills development in children and the reasons why some children who have experienced adversity early in their lives, come to school with “baggage”. It takes a cursory look at the effects of emotional trauma on the developing brain and examines why affected children often demonstrate anti-social behaviour and struggle with forming meaningful relationships and learning in school. Also considered are the problems encountered by some children at the upper end of the socioeconomic spectrum, most particularly their difficulties making friends.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".