Family cohesiveness and delinquency : a study of forty-nine juvenile delinquents from the Halifax Regional Office, Department of Public Welfare, active as of November 1965
Bibliographic record
Abstract
This study investigates the relationship between family cohesiveness and the incidence of delinquency. It is an individual thesis written as one part of a group study, of active files, of the delinquents at the Halifax Regional Office of the Department of Public Welfare, undertaken by ten members of the 1966 class of the Maritime School of Social Work. \nThe records of 49 delinquents at the Halifax Regional Office of the Department of Public Welfare, active as of November 1965, were the source of data. A common schedule was used to collect pertinent information. Data relevant to this individual thesis were then extracted and statistical test of significance (chi-square) carried out. \nIt was found that the family background of recidivists revealed a significantly less degree of reciprocal parental-filial affection and a higher rate of broken homes and family disruption than the family background of non-recidivists. It was concluded that, in order to be of any service in dealing with delinquent behavior, the social worker must know and understand the delinquent in relation to his family.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".