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تحلیل عوامل تبیینکننده و عناصر اثرگذار بر مشارکت شهروندی (موردکاوی اصفهان)
|پژوهشهای جغرافیای انسانی|
|مقاله 10، دوره 52، شماره 4، دی 1399، صفحه 1339-1355 اصل مقاله (707.1 K)|
|نوع مقاله: مقاله علمی پژوهشی|
|شناسه دیجیتال (DOI): 10.22059/jhgr.2019.272917.1007842|
|محمد حسین شریف زادگان* 1؛ حسین قانونی2|
|1استاد توسعة اقتصادی و برنامهریزی منطقهای، دانشگاه شهید بهشتی، تهران|
|2دکترای برنامهریزی شهری و منطقهای، دانشگاه شهید بهشتی، تهران|
|در مقالة حاضر به بررسی مشارکت شهروندی در شهروندان اصفهانی بالای 18 سال پرداخته شده است. عناصر بسیاری بر مشارکت شهروندان اثرگذارند: ساختارهای سیاسی، شرایط اقتصادی، ویژگیهای فرهنگی، و ... اما حتی اگر زمینههای مشارکت از سوی تصمیمگیران فراهم شود، تا زمانی که شهروندان برای مشارکت در امور مرتبط با زندگی آنان تمایلی نداشته باشند، فرایندهای مشارکتی شکست میخورند. از همین رو، شناسایی عناصر مؤثر بر مشارکت شهروندی میتواند زمینة اجرای مداخلات نهادی برای بهبود مشارکت شهروندی را فراهم کند؛ امری که مسئلة اصلی مقالة پیش روست. برای سنجش مشارکت شهروندی در شهروندان اصفهان 11 گویه انتخاب شد. نمونهگیری بهصورت خوشهای و با حجم نمونة 450 نفری انجام گرفت. علاوه بر گویهها، ویژگیهای بافتاری همچون سن، جنسیت، تحصیلات، شغل، نوع واحد مسکونی، نوع تملک واحد مسکونی، درآمد، مذهب، و قدمت سکونت نیز جمعآوری شد. سپس، با استفاده از نرمافزار SPSSپایایی پرسشنامه با آلفای کرونباخ 680/0 تأیید شد. تحلیل عاملی به شناسایی سه عامل (با مجموع تبیین واریانس 65 درصد) انجامید: «تعهد مدنی»، «تعهد فردی»، و «مشارکت در انتخابات». با ترکیب وزنی عوامل، شاخص «مشارکت شهروندی» محاسبه شد و درنهایت نقشة توزیع شاخص مشارکت شهروندی و عوامل آن در مناطق پانزدهگانة اصفهان ترسیم شد. برای سنجش اثر ویژگیهای بافتاری بر مشارکت شهروندی، از مدلسازی معادلات ساختاری با نرمافزار SmartPLS استفاده شد. نتایج مدلسازی بیانگر آن است که عناصر بافتاری تحصیلات (217/0)، سن (162/0)، و موقعیت شغلی (101/0) با عامل «مشارکت در انتخابات» و «قدمت سکونت» (122/0)، «مذهب» (123/0)، و «نوع تملک واحد مسکونی» (122/0-) با عامل «تعهد مدنی» رابطة معنادار داشتهاند.|
|اصفهان؛ تحلیل عاملی؛ تعهد شهروندی؛ مدلسازی معادلات ساختاری؛ مشارکت شهروندی|
|عنوان مقاله [English]|
|Analysis of the Explaining Factors and Contributing Features of Citizen Participation (Case Study: Isfahan)|
|Mohammad Hossein Sharifzadegan1؛ Hossein Ghanouni2|
|1Professor of Urban & Regional Planning, Urban and architectural studies faculty, Shahid Beheshti University, Tehran.|
|2PhD Graduate in Urban &amp; Regional Planning, Shahid Beheshti University, Tehran.|
This article studies citizen participation of Isfahan citizens over 18 year old. The concept of articipation is as old as humankind and has taken different forms in different periods of history. Since the 1970s, social sciences’ scholars have increasingly emphasized that citizen participation in public decision-making is an important strategy for enhancement of democracy and improving development results. Then, these thoughts were introduced in the urban planning field and have become a hot topic in theoretical and practical debates of the field. Many features influence citizen participation: political structures, economical situations, cultural and historical specifications, etc. However, even if the politicians and decision-makers embrace participation and make it possible from the top, there will be no success in in participatory processes if citizens have no interest in participating. This is the reason why identification of influential features on citizen participation can provide the basis for institutional intervention in order to improve participatory processes, which is the main concern of this article.
For measurement of citizen participation in Isfahan, 11 statements were selected after reviewing the theoretical and practical literature and corresponding indicators. Two examples of statements are: “I’m not much interested in issues not concerning me and my family” and “I have sufficient ability and self-confidence to join parties and political groups”. The alternatives of answers were designed in 5- point Likert-type scale. Based on the statements, these alternatives were “strongly agree”, “agree”, “indifferent”, “disagree”, “strongly disagree” or “too much”, “much”, “middle”, “little” and “too little”. The statistical population is Isfahan citizens of over 18 years old. The sample was chosen by clustering method: at first for every city district, three blocks were chosen randomly and amongst those, accidentally selected people were asked to answer to the questionnaire. The sample size is 450 people, which is more than what Cochran’s formula suggests. The sample is distributed in a way that 30 people represent each district. In addition to the statements, the contextual features were asked from sample population, namely age, gender, education, job status, housing type, tenure type, household income, religiosity and years of residence.
Results and Discussion
After entering and sorting questionnaire data in SPSS, reliability and validity tests were conducted using Cronbach’s Alpha and Factor Analysis, respectively. First, Cronbach’s alpha was calculated for all the statements. Since the score was not acceptable (0.580), two statements were omitted, which resulted in an alpha score of 0.680 and approved the reliability of the questionnaire. Nine remaining statements were analyzed by factor analysis to test construct validity of data and identify explaining factors of citizen participation. Factor analysis -which was conducted by the Varimax rotation method and factors with eigenvalues of over 1.0 acceptance threshold, extracted three factors from nine statements. The factors explained 32, 18 and 16 percent (in total 65 percent) of variation of the citizen participation concept. These factors were named “civic engagement”, “personal engagement” and “participation in elections”. The citizen participation indicator was calculated by a weighted combination of three factors, in which weighing was based on the variance explained by each factor. Finally, the distribution map of three factors and citizen participation indicator were drawn for Isfahan 15 districts of Isfahan. The values were categorized into three classes by half-sigma method, namely “low”, “average” and “high” values.
The maps show that District 2 has the least citizen participation by four “little” values. After that, District 6 & 12 stand with three “little” and Districts 4, 5, 7 & 11 by two “little” values. No district showed “high” values in all 4 variables, but District 9, 10 & 14 showed the best citizen participation by three “high” values. District 3, 4 & 12 were second best by two “high” values.
For measurement of the effects of contextual features on citizen participation, Structural Equation Modeling was conducted by SmartPLS software package. Modelling results show that household income, socioeconomic status, housing type and gender have no significant effect on citizen participation. The factor “personal engagement” showed no significant relation to contextual features. Education (0.217) was shown to be the most influential feature on citizen participation (via “participation in elections” factor). After education, age had the most effect on “participation in elections” factor. Contextual features of “years of residence” (0.122), religiosity (0.123) and “tenure type” (-0.122) were next influential features on citizen participation (via “civic engagement” factor). The least significant relation was reported to be between job status and “participation in elections” factor. In total, contextual features explained 3.4% and 7.8% of the variations of “civic engagement” and “participation in elections” factors, respectively.
The results of this article indicate that improving citizen participation is not just about the contextual features. Although general characteristics of citizens such as educational level and religious beliefs have a significant effect on their participation, the extent of this effect is minimal. this This article shows that contextual features are not decisive factors in citizen participation, but this is “civic engagement” and “personal engagement” of citizens explains more than half of the variations of citizen participation. Therefore, if the decision-makers want to increase civic and personal engagement of citizens successfully, they should make public participation a part of their routine process. To that end, facilitation and policymaking for increase on membership rates of political parties and activities, allowing peaceful protestations to be held, and give liberty to campaigns and social non-governmental institutions can have significant effects on improvement of citizen participation. Moreover, raising awareness of citizens about the important role of personal activities in increasing public benefits (especially environmental activities) can have an influential effect on citizen participation. Finally, although participation in elections apparently is a decisive determinant of citizen participation, the results of this article show that this factor can just explain 15% of the variations of citizen participation. Compatible to theoretical views, this result shows that citizen participation is much more than just representative democracy and has many aspects for consideration. Maybe the temporary nature of participation in election and continuity of civic and personal engagement is the reason why participation in elections is the last explaining factor for citizen engagement.
|Citizen participation, citizen engagement, factor analysis, structural equation modelling, Isfahan|
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