What Motivates Employer Engagement? Promoting Youth Career Embeddedness in Two Tennessee Regions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While workforce development can create skilled workers and better jobs, employer engagement is often limited. This article analyzes the case of Tennessee Pathways and draws on interviews with highly engaged employers, including those that hosted youth worker interns. The author investigates how employers accounted for their involvement and how program design shaped the benefits they perceived. Despite a traditional focus on skills gaps, the author finds that most employers sustained their engagement due to workforce challenges rooted in a mismatch between new hires’ expectations and the realities of the job, which resulted in high turnover of incumbent adult workers. Employers perceived that youth programs addressed this issue by fostering “career embeddedness” and deepening youth workers’ commitment to a nascent career interest or by redirecting them to other viable options. The author argues that practitioners should promote the potential of workforce development to yield long-term workforce reproduction and next-generation career development.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it