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Record W1579782299 · doi:10.5367/ihe.2015.0252

What Students Want: Elements of Job Satisfaction Expectations among Multicultural Cohorts

2015· article· en· W1579782299 on OpenAlexaboutno aff
Dannie L. Brown

Bibliographic record

VenueIndustry and Higher Education · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsJob satisfactionRanking (information retrieval)PsychologySocial psychologyNova scotiaMulticulturalismDemographic economicsApplied psychologySociologyPedagogyEconomics

Abstract

fetched live from OpenAlex

The purpose of this research was to assess students' expectations of future job satisfaction. Data were collected from 484 students enrolled in the BBA programme at Cape Breton University, Nova Scotia, Canada. Locke's job satisfaction theory and Hackman and Oldham's job characteristics model provided the theoretical foundation for the study. Kendall's W was used to determine the degree of agreement between the current results and earlier research results and mean ranking was applied to determine the respondents' Top 10 expectations. One Way Anova was used to determine the differences among the multicultural cohorts. While each cohort had similar expectations by ranking, some cultural differences were evident. The results also indicate that today's students have different expectations for job satisfaction than employees of a generation ago. These findings may help employers prepare for the new employees they will hire through a foreknowledge of the new recruits' expectations of job satisfaction.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.309
Teacher spread0.279 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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