The Adverse Childhood Experiences of Methamphetamine Users in Aotearoa/New Zealand
Bibliographic record
Abstract
Using in-depth semi-structured interviews, the family environment of forty-one former frequent methamphetamine users is analyzed using a ten category measure of adverse childhood experiences (ACEs). The qualitative analysis reveals almost three-quarters experienced four or more ACEs, especially parental separation, parental substance abuse, emotional neglect and physical neglect. Females compared to males, and Māori compared to European/Pākehā, experienced more adversity, while father figures played a disproportionate role in producing participants’ childhood adversity. Physical neglect, physical abuse, parental mental illness, sexual abuse and early age of parental separation were especially detrimental to participants’ healthy development. With approximately five ACEs each on average, this first ever life course-based qualitative study of frequent methamphetamine users in Aotearoa/New Zealand adds further evidence to the body of knowledge that demonstrates frequent substance use is an adaptive counterproductive coping mechanism to adverse childhood experiences. However, six interviewees were exposed to none or one ACE. With ‘good’ and ‘fortunate’ childhoods, and loving and supportive parents, such contrary childhoods underscore the importance of cultivating and practicing prosocial authoritative parenting practices.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".