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Record W2900895202 · doi:10.1177/1539449218813702

Competence and Satisfaction in Occupational Performance Among a Sample of University Students: An Exploratory Study

2018· article· en· W2900895202 on OpenAlexaboutno aff
Karen M. Keptner, Rachel Rogers

Bibliographic record

VenueOTJR Occupational Therapy Journal of Research · 2018
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
FundersCleveland State University
KeywordsCompetence (human resources)PsychologyEthnic groupJob satisfactionSignificant differenceSocial psychologyGerontologyMedicineSociology

Abstract

fetched live from OpenAlex

Success at university may be influenced by concerns with occupation and occupational performance. To understand occupations of concern and occupational performance among a sample ( N = 144) of university students in the Midwest United States, the Canadian Occupational Performance Measure was administered. Socially related ( n = 103), academic-related ( n = 75), and work-related ( n = 64) occupations were the three most frequently reported occupational concerns. Time management ( n = 79) was the most frequent person-level concern. Mean self-perceived competence in occupations was 29.83 ( SD = 7.18) out of 50 and mean performance satisfaction was 26.80 ( SD = 8.01) out of 50. There were no differences in occupational performance across gender, race/ethnicity, class standing, living environment, or work status. However, within participants, there was a significant and clinically relevant difference between performance satisfaction and self-perceived competence in occupation, t(143) = 7.052, p < .0005, d = 0.58. Students have varied occupations that they find important, and future research should explore how occupational performance and performance satisfaction influence university success.

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)0.012
metaresearch head score (Gemma)0.001
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 score0.014
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.283
GPT teacher head0.547
Teacher spread0.264 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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