A Nexus between Project Management Lifecycle and Performance of Slums Upgrading Projects in Nairobi City County, Kenya
Bibliographic record
Abstract
The alarming rate of urban sprawl poses a social menace for city planners and governments worldwide and Nairobi city of Kenya is not an exception. Challenges of access to appropriate and affordable housing has forced majority of city residents to occupy shanties with deplorable living conditions thus, the need to improve the infrastructure in the slums. In Kenya, the government has initiated various projects in a bid to carry out a facelift of slums countrywide. Although, involvement of key stakeholders in each of the phases of project management lifecycle (PMLC) that is, project initiation, planning, implementation, Monitoring & evaluation and closure remains a critical factor to the realization of slum upgrading infrastructure development, the affected communities are not fully engaged thus thwarting effective implementation of the planned activities. In this regard, the aim of the study was to examine the influence of PMLC on performance of slums upgrading projects (PSUP). A descriptive survey research design and a correlational research design were utilized whereby data was analysed and interpreted using means, standard deviations, correlation of coefficient and correlation of determination. A sample of 266 was drawn from a target population of 794, of which 208 responded to a 5-point Likert Scale questionnaire. Qualitative data collected was presented in narrative form. Results obtained indicated a linearly positive and a very strong significant relationship between PMLC and PSUP. When all phases were combined PMLC explained 62.9% of the overall variation in PSUP. The findings indicate that a unit increase in initiation and planning stages result to an increase in PSUP by 7.77% and 1.97% respectively whereas for a unit decrease in project implementation and project M&E, PSUP decreases by 2.07% and 1.72% respectively. It was thus concluded that PMLC significantly influences Performance of Slum Upgrading Projects. The recommendation of the study was that activities pertaining to project planning, M&E and project closure phases be efficiently executed for optimum performance of the projects.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".