Violence against the adolescents of Kolkata: A study in relation to the socio-economic background and mental health
Bibliographic record
Abstract
This study attempts to understand the nature of violence suffered by the adolescents of Kolkata (erstwhile Calcutta) and to identify its relation with their socio-economic background and mental health variables such as anxiety, adjustment, and self-concept. It is a cross-sectional study covering a total of 370 adolescents (182 boys and 188 girls) from six higher secondary schools in Kolkata. The data was gathered by way of a semi-structured questionnaire and three standard psychological tests. Findings revealed that 52.4%, 25.1%, and 12.7% adolescents suffered psychological, physical, and sexual violence in the last year. Older adolescents (aged 17–18 years) suffered more psychological violence than the younger ones (15–16 years) (p < 0.05). Sixty nine (18.6%) adolescent students stood witness to violence between adult members in the family. More than three-fifth (61.9%) adolescents experienced at least one type of violence, while one-third (32.7%) experienced physical or sexual violence or both. Whatever its nature is, violence leaves a scar on the mental health of the victims. Those who have been through regular psychological violence reported high anxiety, emotional adjustment problem, and low self-concept. Sexual abuse left a damaging effect on self-concept (p < 0.05), while psychological violence or the witnessing of violence prompted high anxiety scores (p < 0.05), poor emotional adjustment (p < 0.05), and low self-concept (p < 0.05). This study stresses the need to provide individual counselling services to the maltreated adolescents of Kolkata so that their psychological traumas can heal and that they can move on in life with new hopes and dreams.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".