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Record W2587789552 · doi:10.21083/ajote.v5i1.3512

AN ASSESSMENT OF PREPARATION LEVEL, SURVIVAL SKILLS, AND ENTREPRENEURIAL KNOWLEDGE AMONG RETIRED TEACHERS IN ZAMBIA

2017· article· en· W2587789552 on OpenAlexvenueno aff
Robinson Mambwe, Chisha Mwape

Bibliographic record

VenueAfrican Journal of Teacher Education · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsNonprobability samplingCivil servantsEntrepreneurshipLife skillsFinancial literacyBusinessPsychologyMedical educationPedagogySociologyPolitical scienceFinanceMedicine

Abstract

fetched live from OpenAlex

This study investigated the preparation level, survival skills, and entrepreneurial knowledge among retired teachers in Zambia, as well as the success of their post-retirement business ventures. Descriptive survey design utilising both quantitative and qualitative methods were employed through use of questionnaires and semi-structured interviews. Convenient and purposive sampling techniques were utilised in sampling. The conclusion shows that most retired teachers lack survival and entrepreneurial skills to manage their business ventures. Lack of pre-retirement entrepreneurial training, lack of pre-retirement counselling, and poor planning for retirement life were found to be the major hindrances to retired teachers’ success in managing their business ventures. The article points to the need for major reforms in teacher training and in pensions scheme policies in Zambia to accommodate issues of financial literacy and entrepreneurial skills among teachers as a way of preparing teachers and other civil servants for life after formal employment.

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)0.000
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 score0.021
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.029
GPT teacher head0.351
Teacher spread0.322 · 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
Published2017
Admission routes1
Has abstractyes

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