A longitudinal examination of the self-medication hypothesis : the impact of self-medication on the development of anxiety, substance use and comorbidity in a nationally representative sample
Bibliographic record
Abstract
A Thcsis/Pr'¿rcticum submitted to the Fircultl, of Gl.atluate Studies of Tttc Univct.sityol Manitob¿r in ¡r:rrtial fì¡lfillment of thc requirernent of the dcgree of Master of Arts Jennif'er A. RobinsonO2009 Pcrnrissiolt h¿rs been granted to the Unir,er.sit)'ol.Nllanitobt Libr¿u-ies to lend ¿r copy of this thesis/practicum, to LibrarS, and Archivcs C¿rn:rtla (LAC) to lend ¿ì copy of this thcsis/pr:rcticum, and to LAC's agent (UMI/ProQuest) to microfilm, sell copics ¿rnd to ¡rublish ¿rn ¿rþstr¿rct of this thcsis/¡rracticu m.This re¡rrotluctiolt ot' cop\/ of this thesis h¿rs bee n mirrlc ¿rr,¿ril¿rþle þ\' authorit¡' of t¡e copyright o\\/ncr solel¡' 1¡¡' the ¡rur'¡rose of ¡lrir':rte sturlv and rescarch, irnd may onlv bc l.e¡rr.oduced,inrl copied :rs pcrmittccl b1' co¡lvrigltt lan's ot'rvith exllress u,ritfen ¿uthol'iz¿rtion fl'om t¡e cg¡¡,right o*,uer.B),
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".