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Junior Faculty Engagement at iSchools: Personal Experience during the First Several Years

2009· article· en· W9488056 on OpenAlexaboutno aff
Phillip M. Edwards, W. John MacMullen, Scott Paquette, Megan Winget

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsChapelSociologyVariety (cybernetics)Higher educationLibrary scienceMedical educationPedagogyPolitical scienceMedicineHistory

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.245
GPT teacher head0.524
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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