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Record W2149624332 · doi:10.1177/0020715208093080

Field of Study and Students' Workload in Higher Education

2008· article· en· W2149624332 on OpenAlexvenueno aff
Merike Darmody, Emer Smyth, Martin Unger

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsWorkloadContext (archaeology)Perspective (graphical)Higher educationField (mathematics)InstitutionPsychologyPerceptionMathematics educationSociologyComputer sciencePolitical scienceSocial scienceGeographyMathematics

Abstract

fetched live from OpenAlex

There is a growing recognition of the importance of `field of study' in social research. However, few of the existing studies explore the extent to which different fields of study facilitate or constrain opportunities to engage in employment and students' perceptions of their work load in higher education. This article aims to explore the workload of higher education students across different fields of study in comparative perspective. Contrasting Ireland and Austria enables us to explore the way in which the institutional context influences student workload. Analyses of the survey data were conducted to explore the extent to which field of study influenced time spent at formal classes, on personal study and in term-time employment. Regression models were used to estimate the effect of field of study, controlling for a number of factors, including higher education institution, personal characteristics and other potential constraints on student time. Finally, we analyse the effect of student workload on overall satisfaction levels.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.312

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 studies0.0000.000
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 head0.078
GPT teacher head0.467
Teacher spread0.388 · 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 teacher head, 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

Citations19
Published2008
Admission routes1
Has abstractyes

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