A Study on the Experiences of College Student Mentors Participating in Community Networks Youth Career Experience Programs- Focusing on the Case of “Ggumridan-gil”
Bibliographic record
Abstract
The purpose of this study is to examine the characteristics of youth career experience programs in connection with the local community and to examine their meaning based on the experiences of university student mentors who participated in the "Ggumridan-gil " program. For this purpose, in-depth interviews were conducted with 8 university student mentors who participated in the "Ggumridan-gil " program. 15 topics and 6 categories were derived based on the collected interview contents. First, the "Ggumridan-gil" program, in which teenagers took part, first and foremost signifies "restoring the essence of career experience," which has been validated as a "professional education" and shown to be a program that permits easy "rapport formation" between youth and adults. On the other hand, it was found that university student mentors were in charge of the role of "supporters and guides" and experienced "growth and change" with youth mentees who participated in the program. And it was found that the youth who participated in the program had a special experience of 'community support'. Based on these research results, this study suggested that the " Ggumridan-gil" program can be a new model for youth career experience education based on connection and cooperation with the local community.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".