Junior Faculty Engagement at iSchools: Personal Experience during the First Several Years
Bibliographic record
Abstract
This roundtable discussion will explore how junior faculty at iSchools have been able to embed their research, teaching, and service activities within their schools, the larger institutions, and broader communities. The session will also focus on the ways in which junior faculty have received guidance in their roles--from the job search through the first several years in a tenure-track position. Roundtable leaders represent a variety of institutions and experiences--as faculty at the University of Illinois at Urbana-Champaign [WJM], the University of Maryland [SP], the University of North Carolina at Chapel Hill [PME], and the University of Texas at Austin [MW], and with doctoral-level preparation at the University of North Carolina at Chapel Hill [WJM, MW], the University of Toronto [SP], and the University of Washington [PME]. While the annual junior faculty mentoring event at the iConference specifically targets junior faculty as participants, this roundtable session offers a more inclusive environment for the discussion of this topic, specifically engaging doctoral students and senior faculty as well as their junior colleagues.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.004 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".