Legal Frameworks, Political Environment and Performance of Biosocial Projects in Informal Settlements in Nairobi County, Kenya
Notice bibliographique
Résumé
This scholarly work studied Legal frameworks, political environment and performance of biosocial projects in informal settlements in Nairobi County, Kenya. Purpose of this scholarly work was to ascertain political environment moderate’s relationship between legal frameworks and performance of biosocial projects in informal settlements in Nairobi County, Kenya. The variable indicators were derived from legal frameworks and political environment indicators as independent variables against performance of biosocial projects indicators as dependent variable of this scholarly work. The study was premised on project theory for the two independent variables and for the dependent variable theory of constraint. In this study Pragmatism and mixed research approach were embraced to examine political environment, legal frameworks and performance of biosocial projects while descriptive and correlational research designs were adopted. Self dispensed questionnaires were administered to gather quantitative data while interview guides were used to collect qualitative data after the pilot testing of research instruments to test validity through content related method and reliability through test-retest criterion. A sample size of 183 individuals from 61 biosocial projects were selected from a target sample of 70 biosocial projects in Nairobi County through Gakuu, Kidombo and Keiyoro, 2016 sampling formula (s= (z/e)2). Quantitative data was computed from structured questionnaires administered to 61 staff members working in the selected biosocial projects and 61 beneficiaries from the biosocial projects besides qualitative in- depth interviews with 61 key informants from State and non-state actors through purposive sampling technique. The statistical tools of analysis that were used were arithmetic mean and the standard deviation for descriptive data whereas Pearson’s Product Moment Correlation (r) in addition to Stepwise Regression (R2) were used as inferential statistics tools of analysis, hypothesis was tested by use of F-tests. To avoid invalidation of statistical analysis, tests of statistical assumptions were carried out before data analysis. From the data analysis the null hypothesis that stated the relationship between legal frameworks and performance of biosocial projects in informal settlements in Nairobi County is not moderated by political environment was accepted with F = 15.207, p =0.000<0.05, r = 0.382, Adjusted R2 = 0.136 in step one against step two where F = 6.263, p =0.000<0.05, r = 0.390, Adjusted R2 = 0.128 and concluded that Adjusted R2 decreased from 0.136 to 0.128 and F statistics reduced from 15.207 to 6.263 the effect of relationship of legal frameworks on performance of biosocial projects.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».