Social Capital Measurement in Turkiye: Creating an Index by Province

Abdulmuttalip Pilatin; Hasan Ayaydın

Makale detayları

Social Capital Measurement in Turkiye: Creating an Index by Province

Yazarlar:

Abdulmuttalip Pilatin | Hasan Ayaydın

Yayıncı:

Istanbul University

Ana Başlıklar:

Sosyoloji

Dergi:

Journal of Economy Culture and Society Issue 66, pp.235-259

Belge Tipi:

Makale

Yayın Tarihi:

1/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001282579

pISSN:

2645-8772

Anahtar kelimeler:

Özet:

 The aim of the study is to create a social capital index on the basis of 81 provinces covering the years between 2007-2018 in Turkiye. While creating the social capital index, the method of creating the social capital index obtained from 2 networks and 2 norm variables, which was also used in previous studies, was applied. While the number of foundations and associations on a provincial basis was used as network variables, the rate of voting in parliamentary elections and the rate of response to WVS surveys were used as norm variables. In order to perform principal component analysis, the collected data was entered into the SPSS 23 package program, and the relevant analysis was performed. For this purpose, principal component analysis was applied for the years 2007, 2011, and 2018, when parliamentary general elections were held, and the first component that emerged was taken as an indicator of social capital index. Since social capital does not change in a short period of time for countries, regions, and cities, the index values for the years between 2007, 2011 and 2018 were created with the linear interpolation method using the data, as applied in similar studies. Positive ones among the index values created on the basis of provinces indicate a high level of social capital, while negative values indicate a low level of social capital. When the social capital index values of 2007 and 2018 are examined, it is observed that the social capital levels of the provinces have increased over the years, although there has not been much change in the index values on a provincial basis over the years.

 The aim of the study is to create a social capital index on the basis of 81 provinces covering the years between 2007-2018 in Turkiye. While creating the social capital index, the method of creating the social capital index obtained from 2 networks and 2 norm variables, which was also used in previous studies, was applied. While the number of foundations and associations on a provincial basis was used as network variables, the rate of voting in parliamentary elections and the rate of response to WVS surveys were used as norm variables. In order to perform principal component analysis, the collected data was entered into the SPSS 23 package program, and the relevant analysis was performed. For this purpose, principal component analysis was applied for the years 2007, 2011, and 2018, when parliamentary general elections were held, and the first component that emerged was taken as an indicator of social capital index. Since social capital does not change in a short period of time for countries, regions, and cities, the index values for the years between 2007, 2011 and 2018 were created with the linear interpolation method using the data, as applied in similar studies. Positive ones among the index values created on the basis of provinces indicate a high level of social capital, while negative values indicate a low level of social capital. When the social capital index values of 2007 and 2018 are examined, it is observed that the social capital levels of the provinces have increased over the years, although there has not been much change in the index values on a provincial basis over the years.

 The aim of the study is to create a social capital index on the basis of 81 provinces covering the years between 2007-2018 in Turkiye. While creating the social capital index, the method of creating the social capital index obtained from 2 networks and 2 norm variables, which was also used in previous studies, was applied. While the number of foundations and associations on a provincial basis was used as network variables, the rate of voting in parliamentary elections and the rate of response to WVS surveys were used as norm variables. In order to perform principal component analysis, the collected data was entered into the SPSS 23 package program, and the relevant analysis was performed. For this purpose, principal component analysis was applied for the years 2007, 2011, and 2018, when parliamentary general elections were held, and the first component that emerged was taken as an indicator of social capital index. Since social capital does not change in a short period of time for countries, regions, and cities, the index values for the years between 2007, 2011 and 2018 were created with the linear interpolation method using the data, as applied in similar studies. Positive ones among the index values created on the basis of provinces indicate a high level of social capital, while negative values indicate a low level of social capital. When the social capital index values of 2007 and 2018 are examined, it is observed that the social capital levels of the provinces have increased over the years, although there has not been much change in the index values on a provincial basis over the years.

 The aim of the study is to create a social capital index on the basis of 81 provinces covering the years between 2007-2018 in Turkiye. While creating the social capital index, the method of creating the social capital index obtained from 2 networks and 2 norm variables, which was also used in previous studies, was applied. While the number of foundations and associations on a provincial basis was used as network variables, the rate of voting in parliamentary elections and the rate of response to WVS surveys were used as norm variables. In order to perform principal component analysis, the collected data was entered into the SPSS 23 package program, and the relevant analysis was performed. For this purpose, principal component analysis was applied for the years 2007, 2011, and 2018, when parliamentary general elections were held, and the first component that emerged was taken as an indicator of social capital index. Since social capital does not change in a short period of time for countries, regions, and cities, the index values for the years between 2007, 2011 and 2018 were created with the linear interpolation method using the data, as applied in similar studies. Positive ones among the index values created on the basis of provinces indicate a high level of social capital, while negative values indicate a low level of social capital. When the social capital index values of 2007 and 2018 are examined, it is observed that the social capital levels of the provinces have increased over the years, although there has not been much change in the index values on a provincial basis over the years.

Makale detayları

Social Capital Measurement in Turkiye: Creating an Index by Province

Yazarlar:

Abdulmuttalip Pilatin | Hasan Ayaydın

Yayıncı:

Istanbul University

Ana Başlıklar:

Sosyoloji

Dergi:

Journal of Economy Culture and Society Issue 66, pp.235-259

Belge Tipi:

Makale

Yayın Tarihi:

1/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001282579

pISSN:

2645-8772

Social Capital Index

Principal Component Analysis

Linear Interpolation

Turkiye

Sayı

Makale detayları

Social Capital Measurement in Turkiye: Creating an Index by Province

Yazarlar: Abdulmuttalip Pilatin | Hasan Ayaydın

Yayıncı: Istanbul University

Ana Başlıklar: Sosyoloji

Dergi: Journal of Economy Culture and Society Issue 66, pp.235-259

Belge Tipi: Makale

Yayın Tarihi: 1/2023

Belge Dili: İngilizce

Document ID (Org No.): 2001282579

pISSN: 2645-8772

Social Capital Index

Principal Component Analysis

Linear Interpolation

Turkiye

Sayı

Yazarlar:

Abdulmuttalip Pilatin | Hasan Ayaydın

Yayıncı:

Istanbul University

Ana Başlıklar:

Sosyoloji

Dergi:

Journal of Economy Culture and Society Issue 66, pp.235-259

Belge Tipi:

Makale

Yayın Tarihi:

1/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001282579

pISSN:

2645-8772