ALCOHOL ABUSE, INCOME AND THE LABOUR MARKET EXPERIENCE
Bibliographic record
Abstract
In 2002, an estimated $39.8 billion was attributed to the economic costs of substance abuse (Rehm et al., 2006). Almost two-thirds of these costs are estimated to be due to losses in labour productivity. However, much debate exists as to the extent and exact mechanisms that lead to problem drinking. As such, there is little consensus as to the effects it has on income, wages, and labour market supply. Many studies have focused on the impact of income on problem drinking, rather than its effects on employment and labour supply. This paper will investigate the impact of problem drinking on income and employment in Saskatchewan by using Canadian Community Health Survey data from 2005. A bivariate probit model was used to control for possible correlation surrounding the factors that affect employment, income and problem drinking. I find an insignificantly positive impact of problem drinking on employment and income for men and an insignificantly negative impact of problem drinking on employment and income for women. These findings are consistent, to a degree, with other research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".