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An Empirical Study of Career Orientations and Turnover Intentions of Information Systems Personnel in Botswana

2012· book-chapter· en· W2487952620 on OpenAlexaff
K.V. Mgaya, Faith‐Michael Uzoka, E.G. Kitindi, A.B. Akinnuwesi, Alice P. Shemi

Bibliographic record

VenueIGI Global eBooks · 2012
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsMount Royal University
Fundersnot available
KeywordsTurnover intentionPerspective (graphical)PsychologyJob satisfactionCareer developmentTurnoverSocial psychologyService (business)Developing countryDemographic economicsManagementBusinessMarketingEconomic growthEconomics

Abstract

fetched live from OpenAlex

A number of studies on career orientations of information systems (IS) personnel have focused on developed countries. This study attempts to examine career anchors of IS personnel from the perspective of a developing country, Botswana. The results of the study show that IS personnel in Botswana exhibit career orientations similar to those identified in literature. However, there are some variations, which are attributed to cultural and socio-economic peculiarities. The study indicates that life style does not feature as a significant career anchor in Botswana. The dominant career anchors include organizational stability (security) and sense of service (service). Gender, age, and educational qualifications tend to moderate the career anchors significantly; thus creating a partition of the anchors across demographic groups. The major contributors to the turnover intentions of IS personnel in developing economies are job satisfaction and growth opportunities. Career satisfaction, supervisor support, organization commitment, length of service, and age did not contribute significantly to turnover intention.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.697

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 communication0.0000.001
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 head0.027
GPT teacher head0.267
Teacher spread0.239 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

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