Relationships between personal, environmental, organisational factors and citizen participation in neighborhood council Tehran, Iran
Notice bibliographique
Résumé
The study was designed to determine the relationship between personal,environmental and organizational factors and citizen participation in neighborhood councils in Tehran, Iran. Citizen participation play a relevant role in many community settings, but the major puzzle was the lack of resident participation which threatened potential success of efforts at the local level. A conceptual model was developed to identify relationships between personal, environmental and organizational factors that contribute to citizen participation. Each of the factors included several variables. In order to achieve the goals of study, a cross sectional survey design was applied and the data were gathered through personal interviews using a set of questionnaires. The data were collected from 250 respondents which were randomly selected from five neighborhood councils in Iran. Descriptive analysis,Pearson product moment correlation and structural equation modeling (SEM) were employed for analyzing the data. The findings of descriptive study showed that the majority of the respondents were female (57.2%) and single (60.8%). Mean of the respondent‘s age was 36 years and the average total monthly income was 3.5 million Rials per month. The study showed that 43.6% of respondents had completed or obtained a bachelor‘s degree. More than three quarter (64%) of respondents had a job, while 35.2% of respondents were unemployed. The average duration of participation in neighborhood councils was two years and four months. Only 41.6% of respondents stated their position as active participants in neighborhood councils. The most important residents‘ sources of knowledge on neighborhood council activities were through their friends/neighbors (48.8%). The study also showed that the level of citizen participation in neighborhood councils was moderate; however, citizens preferred greater involvement in social and environmental rather than economicalactivities. Pearson‘s correlation analysis showed that there was a high positive correlation between perceived knowledge, organizing skills and sense of community with citizen participation; while there was a medium positive correlation between selfefficacy, perceived trust, organizational factors and norms for activism with citizen participation; and finally there was a small and positive correlation between neighborhood problems and citizen participation. The results of hypotheses testing with the structural model showed strong relationships between perceived knowledge, organizing skill, perceived trust, and sense of community and citizen participation. The results of the overall model showed that there were no significant relationship between self efficacy, perceived neighborhood problems and organizational factors. The result also showed that norms for activism cannot mediate between sense of community and citizen participation. Based on the structural equation model the between individual factors, perceived knowledge and between environmental factors sense of community had the most significant contribution in predicting citizen participation. The results of this study also provided some theoretical and practical implications on citizen participation in neighborhood councils. The study recommends social cognitive theory is appropriate to explain factors influencing citizen participation. Several recommendations for improvement with respect to policy and practices of neighborhood council to increase citizen participation are suggested.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».