Structure May Be Key to Incorporating Library School Interns in Academic Library Environments
Bibliographic record
Abstract
Objective – To evaluate the effectiveness of the San Jose State University Library internship program. Design – Focus group; single point in time; qualitative design. Setting – Large academic library in the United States of America. Subjects – Nine former interns of the San Jose State University (SJSU) Library. Methods - Nine former interns of the SJSU Library internship program participated in a single 90-minute session. No inducements for participation were offered. A moderator asked a series of 10 questions designed to gather feedback in three areas: 1) “the internship as part of the Masters program,” 2) “the internship’s role in the realization of personal objectives and professional development,” and 3) “the experience of working in team based activities.” A digital voice recorder captured the participants’ responses, allowing for detailed analysis of the responses after the session. Main Results – The interns deemed their overall experience successful, as all indicated they achieved their professional development objectives for the internship. However, the interns also indicated their experience could have been improved by the appointment of a single dedicated coordinator for recruitment and oversight, as well as more feedback on the quality of their work, especially for course-related instruction. Conclusion – The SJSU Library determined that the internship program was advantageous to both the Library and the interns. All of the interns who participated in the focus group achieved their profession development objectives for the internship. Additionally, the Library received valuable feedback for improving the program. Suggestions included appointing a dedicated internship coordinator, allowing interns more of an opportunity to choose their projects, and ensuring that interns are offered frequent feedback about the quality of their work.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".