Structural Conditions as Cause: Explaining the Rapid Rise in Youth E-Cigarette Use by Re-thinking Models of Addiction
Bibliographic record
Abstract
Background: E-cigarette use has spread rapidly and widely among youth, to an extent that has surprised some researchers.Objectives: We suggest that this surprise is owing to a particular limitation in the dominant models of addiction – namely, a strong focus upon addictive substances as cause. We argue that the phenomenon at hand is easier to comprehend when less attention is placed upon preventing the use of specific substances and more upon what we identify as structural susceptibility to addiction instead.Results: Drawing upon neurobiology, history, public health theory, and social theory, we re-conceive addictive substances as mechanisms of escape from social structures that predispose whole societies to addiction.Conclusions/Importance: We argue that the surge in youth e-cigarette use in particular, as well as the phenomenon of addiction in general, are easier to comprehend if models of addiction are expanded to conceptualize the problem in its wider dimensions. We invite addictions researchers to join us in expanding the field’s analytical view.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.013 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".