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Record W4407746358 · doi:10.1080/13562517.2025.2449642

Caught in a loop? Investigating the interplay between time and emotions for university students

2025· article· en· W4407746358 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTeaching in Higher Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHigher educationPsychologyMathematics educationPedagogySociologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

This article explores the significant yet under-researched relationship between students’ experiences of time and their emotions during university studies. We frame our study through two existing theoretical concepts of time, that of timescapes and time-as-affect, to illuminate the subjective, contextual nature of time and how students’ experiences of time can produce strong emotions, permeating both their memories and future behaviour towards their studies. We adopted a narrative analysis approach to the qualitative data of three Australian undergraduate equity students, collected via in-depth longitudinal interviews and relating to their university experiences, to produce a series of ‘explanatory stories’. These stories highlight the interplay between students’ experiences and emotions of time showcasing how these can form a loop, which may lead to temporal inequities. Ultimately, we argue for greater recognition of the entangled relationship between students’ time and emotions, as we set a path for this critical area of 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.053
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.391
Teacher spread0.360 · 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