Improving Public Service Delivery Through Good Corporate Governance: Lessons From the Embu County Government, Kenya
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Poor service delivery in Embu County, marked by governance lapses, corruption, and inefficiencies, indicates a gap in understanding how corporate governance principles, such as stakeholder inclusivity, transparency, public participation, and accountability, influence effective service delivery in the context of devolved governance. This study therefore sought to examine the effect of stakeholders’ transparency, inclusivity, public contribution, and accountability on service delivery. The theoretical basis for this research was anchored on SERVQUAL Model. The study was in addition underpinned by Agency Theory, Stewardship Theory, and Institutional Performance Theory and Resource-Based Theory. A descriptive survey research design was applied, targeting 248 workers from Embu County from which a sample of 153 respondents was selected using a proportionate stratified and simple random sampling technique. The findings revealed that stakeholders' inclusivity, transparency, public participation, and accountability jointly explained 62.9% of the variation in service delivery in Embu County Government (Adjusted R² = 0.615). Regression analysis showed that stakeholders' inclusivity (β = 0.208, p = 0.020), transparency (β = 0.053, p = 0.007), public participation (β = 0.465, p = 0.000), and accountability (β = 0.164, p = 0.042) were all positively and significantly related to service delivery. The study concludes that stakeholders’ inclusivity, transparency, public participation, and accountability significantly affect service delivery, with public participation having the most substantial impact. In view of the findings, the study recommends that Embu County Government should improve corporate governance practices by institutionalizing structured public participation frameworks, improving financial transparency, and reinforcing stakeholder engagement mechanisms.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it