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Record W3201919056 · doi:10.3311/ope.471

Working and learning? Features of student employment during COVID-19

2021· article· en· W3201919056 on OpenAlexaboutno aff
Zsófia Kocsis

Bibliographic record

VenueOpus et Educatio · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAmbivalenceExploratory researchWork (physics)Quarter (Canadian coin)Coronavirus disease 2019 (COVID-19)PsychologyMedical educationSocial psychologyMedicineSociologySocial science

Abstract

fetched live from OpenAlex

The literature contains ambivalent research findings on the impact of student employment on study careers. Previous findings also indicated that student employment plays a significant role in interrupting study (Kovács et al. 2019). In our exploratory research, we focused on exploring the employment characteristics of university students during COVID -19. The aim of the study is to investigate the impact of the epidemiological situation on young people's work. To what extent did the epidemic change students' attitudes towards work and study? The research involved university students who regularly work alongside their studies. The online survey was conducted between January and March 2021 (N=235). The majority of the students worked during the epidemiological situation. Contrary to our assumptions, they had no major, long-standing financial problems. An important question for educational research is the relationship between work and learning. A quarter of the respondents had work related to their studies. Some of the undivided student teachers may be considered an at-risk group because they had experiences during their employment that made them insecure about their degree. Our results also showed that students who have study-related work are more committed to a degree and less uncertain about finding a job in their chosen profession.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.226
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.053
GPT teacher head0.460
Teacher spread0.408 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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