Bibliographic record
Abstract
The purpose of this qualitative study was to investigate drug offense recidivism among female inmates for which data were collected from in-depth interviews with 18 female inmates of Nakhon Si Thammarat Central Prison, and informal interviews with prison officers or warders. Logical context description was employed to analyze content by comparing theoretical concepts with other related studies.The findings of the study revealed that the recidivism among female inmates would never end if they still had arduous living conditions with burdens of raising children without help from relatives. Most of them were not well educated and were easily cheated by males who were their boyfriends or husbands. It could be because they wanted love, good future, good family, and a lot of money, so they inevitably chose to commit offenses either with or without intention. Most of the female inmates did not learn their lesson if the penalties were not severe. Some of them were granted a royal pardon, which was deemed the best thing that could happen in the life of any inmate, however, they were not afraid of reoffending-even though whilst in prison they intended not to have anything to do with drugs again. Nevertheless, when they returned to the same environments, their way of life and people around them made them repeat their offenses. The results of this study would be useful for related individuals and organizations in forming policy and designating preventive measures, and solving the problem of recidivism so that inmates would become good people and would not repeat the offenses.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".