Green Collar Workers
Bibliographic record
Abstract
OBJECTIVE: We describe the socio-demographic, occupational, and health characteristics of "green collar" workers, a vital and emerging workforce in energy-efficiency and sustainability. METHODS: We linked data from the 2004 to 2012 National Health Interview Surveys (NHIS) and US Occupational Information Network (O*NET). Descriptive and logistic regression analyses were conducted using green collar worker status as the outcome (n = 143,346). RESULTS: Green collar workers are more likely than non-green workers to be men, age 25 to 64 years, obese, and with less than or equal to high school (HS) education. They are less likely to be racial/ethnic minorities and employed in small companies or government jobs. CONCLUSIONS: Green collar workers have a distinct socio-demographic and occupational profile, and this workforce deserves active surveillance to protect its workers' safety. The NHIS-O*NET linkage represents a valuable resource to further identify the unique exposures and characteristics of this occupational sector.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".