Improving School-to-Work Transitions: Antecedents of High-Quality Intern-Supervisor Exchanges
Why this work is in the frame
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Bibliographic record
Abstract
Using a Canadian sample of 146 interns surveyed on three occasions (i.e., before, during, and after their internship experiences), we investigated university students' skills and intentions as critical factors contributing to high-quality intern-supervisor exchanges. Specifically, we sought to better understand how to promote high-quality intern-supervisor relationships by looking at the influences of student-centered factors related to both educational (skills developed while in university) and organizational (intentions to develop relationship with supervisor) domains. To highlight the importance of these factors, we also examined whether their impacts on the quality of intern-supervisor exchanges ultimately translate into better internship outcomes, which we assessed by incorporating perceptions from both interns (i.e., internship satisfaction and general learning) and their supervisors (i.e., interns' in-role performance and preparedness for work). Consistent with expectations, we found that both students' skills developed while in university and students' intentions to develop the relationships with their supervisors were positively related to the quality of intern-supervisor exchanges and, through that pathway, had positive indirect effects on internship satisfaction, general learning, in-role performance, and preparedness for work. Our findings indicate that students, universities, and employers all play a role in the development of high-quality intern-supervisor relationships, which are critical to student learning and performance.
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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 | 0.003 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it