Bibliographic record
Abstract
The general objective of this study is to examine the audit component of human capital management in Nigerian organizations, as a public sector analysis.A specific objective of the work is to make recommendations on the way forward in the effective application of human capital audit as a mechanism of human capital management in the generic Nigerian public sector.Secondary sources of data were utilized in our analysis.Consequently, the work found a very strong linkage between the substandard audit component of human capital management in the country's public sector and the generic dearth of accountability in the Nigerian system.The dual-pronged recommendations of the study are in the following regards.The institution by all public sector organizations in the country an accounting information system that is interactive with the public, to enable the Nigerian tax payers make contributions on how these organizations meet or fail to meet the citizens' needs.Furthermore, the paper recommends the democratization of access to the career data of all public sector individuals in the country, irrespective of ranks, as a mechanism of keeping specific administrations and management organs (in the public sector) on their toes, to reduce the deficiencies in their human capital audit functions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.958 | 0.957 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".