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Record W3164764561 · doi:10.5430/afr.v10n2p51

Human Capital Accounting Implications on Firm Market Value: A Survey of Kenyan Private Universities

2021· article· en· W3164764561 on OpenAlexvenueno aff
San Lio

Bibliographic record

VenueAccounting and Finance Research · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsnot available
Fundersnot available
KeywordsKenyaHuman capitalReputationBusinessValue (mathematics)FinanceAccountingHuman resourcesPrivate sectorEconomicsEconomic growthManagement

Abstract

fetched live from OpenAlex

Purpose-The study examined the findings of an empirical evaluation of Human Capital (HC) accounting implications on firm market value among Kenyan private universities. Design/methodology/approach- a Cross-sectional survey on finance and human resource directors in Kenyan private universities.Findings- Kenyan Chartered Private Universities were successful because they accounted for, and reported their HC as material investments. However, further research was recommended to establish whether: the 4.2% who did not enjoy a good reputation and image consecutively for the past three financial periods; the 47% who did not enjoy easy access to Kenya’s capital markets consecutively for the past three financial periods; the 25% who did not retain their quality HC consecutively for the past three financial periods; as well as the 30% who did not enjoy high ROI consecutively for the past three financial periods: did so solely because they did not account and report their HC as material investments or there were indeed other factors motivating the results. Originality/Value-Accounting for HC is a big deal in Kenyan Knowledge-Information-Service-Sector (KISS) firms such as private universities because HC is the intervening factor for competitive advantage: Yet the discipline is unexplored in existing Kenyan empirical works.

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)0.007
metaresearch head score (Gemma)0.003
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 score0.191
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.096
GPT teacher head0.369
Teacher spread0.273 · 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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