Influence of Critical Success Factors (CSFs) of Housing Co-Operative on Housing Provision in Ogun State, Nigeria
Bibliographic record
Abstract
The purpose of this paper is to identify the Critical Success Factors of housing co-operatives that have a significant influence on the components of housing provision with the view to improving housing delivery.The data were sourced from the co-operative societies involved in the provision of housing in Ogun State through the Ministry of Community Development and Co-operative, located at Oke-Mosan in Abeokuta.The philosophy of the research is positivism and the research approach is quantitative.The study employs the survey method of data collection that makes use of a questionnaire as its research strategy.It involved the administration of 418 copies of a structured questionnaire on the Presidents and members of 52 co-operatives (whose population is 7,496) that responded to the study out of the 56 cooperatives that are engaged in housing provision in Ogun State, Nigeria; using a proportionate sampling method.The data obtained were analysed with the use of Categorical Regression Analysis.The finding showed that adequate participation of members, good quality of housing stock, involvement in building materials production, good corporate governance practices, and very low (1%-5%) management and operational cost are the Critical Success Factors of housing co-operatives that have a significant influence on housing provision.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".