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Record W2793492828 · doi:10.20343/teachlearninqu.6.1.4

Public pedagogy and representations of higher education in popular film: New ground for the scholarship of teaching and learning.

2018· article· en· W2793492828 on OpenAlexaff
K. Johnstone, Elizabeth Marquis, Varun Puri

Bibliographic record

VenueTeaching & Learning Inquiry The ISSOTL Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsMcMaster University
Fundersnot available
KeywordsScholarshipScholarship of Teaching and LearningFraming (construction)SociologyThe artsHigher educationPedagogyTeaching methodMathematics educationTeaching and learning centerArtPsychologyVisual artsPolitical scienceGeography

Abstract

fetched live from OpenAlex

Constructions of teaching, learning, and the university within popular culture can exert an important influence on public understandings of higher education, including those held by faculty and students. As such, they constitute a rich site of inquiry for the scholarship of teaching and learning. Drawing on the notion of film as ‘public pedagogy,’ this article analyses representations of higher education within 11 top grossing and/or critically acclaimed films released in 2014. We identify three broad themes across these texts—the purpose of higher education, relationships between students and professors, and the creation of academic identities—and consider the implications and functions of these representational patterns for teaching, learning, and SoTL. Particular attention is given to the difference between the framing of science and arts and humanities disciplines, and to how this might resonate with the contemporary ‘crisis of the humanities.’

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)0.004
metaresearch head score (Gemma)0.011
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.022
Scholarly communication0.0140.014
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.166
GPT teacher head0.462
Teacher spread0.297 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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