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Record W3172025969 · doi:10.5539/hes.v11n3p43

Who Are Their Leaders? College Students Perceptions of and Engagement with Campus Leaders and Administrators

2021· article· en· W3172025969 on OpenAlexvenueno aff
Stephanie Rizzo, Dana J. Tribble, Louis S. Nadelson

Bibliographic record

VenueHigher Education Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyIntimidationPerceptionExploratory researchFeelingMedical educationLikert scaleQualitative researchHigher educationPublic relationsPedagogySociologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

College students’ interactions with campus leaders is critical to their success, particularly in situations of distress. Yet, little is known about college students’ knowledge, perceptions, and identification of campus administrators, faculty members, and staff as leaders and their interactions with these campus leaders. To fill the gap in the literature, we applied a cross-sectional methodology to gather a combination of quantitative and qualitative data using an online survey. We had 60 first-year students participate in our exploratory research by fully completing our survey. We found that students identified their advisors as leaders on campus. We also found most of our participants avoided campus administrators in fear of judgment, intimidation, and feelings of anxiety. Our results have implications for campus leadership, college administrators, student retention, and campus climate. Following our results, we discuss implications for practice and offer additional recommendations for future research.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.113
GPT teacher head0.462
Teacher spread0.349 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations5
Published2021
Admission routes1
Has abstractyes

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