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Record W2395823930 · doi:10.1080/03075079.2016.1180673

University faculty perceptions and utilization of popular culture in the classroom

2016· article· en· W2395823930 on OpenAlexaff
Jessica Peacock, Ralph Covino, Jessica Auchter, Jennifer Nagel Boyd, Hope Klug, Craig R. Laing, Lindsay Irvin

Bibliographic record

VenueStudies in Higher Education · 2016
Typearticle
Languageen
FieldHealth Professions
TopicFilm in Education and Therapy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPopular cultureHigher educationPerceptionSet (abstract data type)PsychologyCritical thinkingSociologySocial sciencePedagogySocial psychologyMedia studiesPolitical science

Abstract

fetched live from OpenAlex

This article discusses results of a survey on the utilization of and attitudes and beliefs towards the use of popular culture among faculty in higher education. A total of 212 faculty members from a mid-sized public regional university provided responses, with the majority indicating that they utilize popular culture in their classroom teaching with some frequency. Overall, the sample exhibited moderately high levels of confidence in their ability to use popular culture effectively, and found popular culture to be both important to incorporate and beneficial for enhancing critical thinking. Significant differences in both frequency of use and attitudes and beliefs were found among teaching disciplines, with those in Humanities and Social Sciences utilizing popular culture more frequently and having more positive attitudes and beliefs towards popular culture than participants in natural sciences and mathematics. A set of guidelines were provided to help advance the use of popular culture in higher education.

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)0.002
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.244
GPT teacher head0.504
Teacher spread0.260 · 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 designObservational
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

Citations25
Published2016
Admission routes1
Has abstractyes

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