RESULTS OF OPINION SURVEYS RELATED TO KENTUCKY'S CHILD LABOR LAWS
Bibliographic record
Abstract
The authors conducted a study, commissioned by the Child Labor Task Force of the Kentucky Labor Cabinet, of attitudes, opinions, and understandings of the Commonwealth's child labor laws and regulations. Questionnaires were distributed to businesses, unions, students, teachers, and parents. The purpose of the study was to identify problems and concerns with Kentucky's current child labor statutes and regulations. However, based on broad census data, Kentucky is demographically typical of Arkansas, Mississippi and West Virginia. With the whole U.S. and the several states each having an under 18 years-of-age population of about 25–30 percent, Kentucky child labor experience is likely indicative of the entire U.S. This article presents the results of the survey including: where, why and how much students work; the impact of work on school; child labor law violations; and workplace safety and health concerns. Moreover, recommendations for legislative change and further study are presented. Findings indicate that students tend to work in the service industry, with approximately one-half of these employed in restaurants and the remainder in retail or other services. Nearly one-quarter of students are employed in school-related programs including co-op, pre-apprenticeship or school-to-work programs. All but 17 percent work both during the school week and on weekends. Many are working “for money and to pay bills” related to cars, car insurance and spending money. Survey responses and prevailing research indicate a negative impact of too much work on school suggesting the need for re-instituting school-issued work permits. In addition, given that nearly 20 percent of all students responding indicate that they have sought medical care for workplace injuries, and only 37 percent of employers believe that their minor employees understand occupational safety and health rules, key findings suggest an immediate need for re-assessing worker and employer training and education.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".