Výsledky vyhľadávania - "Neighborhood effect"

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    Zdroj: Articles publicats en revistes (Sociologia)
    Dipòsit Digital de la UB
    instname
    Universidad de Barcelona
    Recercat. Dipósit de la Recerca de Catalunya
    Revista Latinoamericana en Ciencias Sociales, Niñez y Juventud, Vol 15, Iss 1, Pp 131-145 (2017)
    Revista Latinoamericana de Ciencias Sociales, Niñez y Juventud, Volume: 15, Issue: 1, Pages: 131-145, Published: JAN 2017

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    Zdroj: Noesis. Journal of Social Sciences and Humanities; Vol. 34 No. 68 (2025); 25-45 ; Nóesis. Revista de Ciencias Sociales y Humanidades; Vol. 34 Núm. 68 (2025); 25-45 ; 2395-8669 ; 0188-9834 ; 10.20983/noesis.2025.2

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    Relation: http://erevistas.uacj.mx/ojs/index.php/noesis/article/view/6853/8648; http://erevistas.uacj.mx/ojs/index.php/noesis/article/view/6853/8565; Anderson, T. W. & Darling, D. A. (1954). A Test of Goodness of Fit. Journal of the American Statistical Association, 49(268), 765–769. https://doi.org/10.1080/01621459.1954.10501232 Anselin, L. (1995). Local Indicators of Spatial Association-LISA. Geographical Analysis, 27(2), 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x Anselin, L. (2019). A Local Indicator of Multivariate Spatial Association: Extending Geary’s c. Geographical Analysis, 51(2), 133–150. https://doi.org/10.1111/gean.12164 Anselin, L. (2024). An Introduction to Spatial Data Science with GeoDa Volume 1 – Exploring Spatial Data (1a ed.). CRC Press. Anselin, L., Bera, A. K., Florax, R. & Yoon, M. J. (1996). Simple diagnostic tests for spatial dependence. Regional Science and Urban Economics, 26(1), 77–104. https://doi.org/10.1016/0166-0462(95)02111-6 Anselin, L. & Rey, S. (1991). Properties of Tests for Spatial Dependence in Linear Regression Models. Geographical Analysis, 23(2), 112–131. https://doi.org/10.1111/j.1538-4632.1991.tb00228.x Anselin, L., Syabri, I. & Kho, Y. (2006). GeoDa: An Introduction to Spatial Data Analysis. Geographical Analysis, 38(1), 5–22. https://doi.org/10.1111/j.0016-7363.2005.00671.x Chua, Ma. C. C. P., Figueroa, L. L. L., Feria, R. P., Cariaga, A. A. D., & Solamo, Ma. R. C. (2019). Spatial analysis of voter turnout in Manila. In Shin-ya Nishizaki, Masayuki Numao, Jaime Caro, & Merlin Suarez (Eds.), Theory and Practice of Computation (1a ed.). CRC Press. Corde, G. W. & Foreman, D. I. (2014). Nonparametric Statistics: A Step-by-Step Approach. John Wiley & Sons. De Haro, L. (2018). Configuración geoespacial del abstencionismo electoral en el Estado de Chihuahua. Geografía y Sistemas de Información Geográfica, 10(10), 52–67. https://dx.doi.org/10.5209/geop.63962 Essletzbichler, J., Moser, M., Derndorfer, J., & Staufer-Steinnocher, P. (2021). Spatial variation in populist right voting in Austria, 2013–2017. Political Geography, 90, 102461. https://doi.org/10.1016/j.polgeo.2021.102461 Esteinou, J. (2019). Las elecciones de 2018 y el triunfo de AMLO/Morena. Argumentos, 32, 13–30. Fiorino, N., Pontarollo, N., & Ricciuti, R. (2022). Detecting Dividing Lines in Turnout: Spatial Dependence and Heterogeneity in the 2012 US Presidential Election. Journal of Geovisualization and Spatial Analysis, 6(2), 6–34. https://doi.org/10.1007/s41651-022-00127-9 Fuentes, C., Peña, S. & Hernández, V. (2018). La medición multidimensional de la pobreza a nivel intraurbano en Ciudad Juárez, Chihuahua (2012). Estudios Fronterizos, 19. https://doi.org/https://doi.org/10.21670/ref.1801001 Geary, R. C. (1954). The Contiguity Ratio and Statistical Mapping. The Incorporated Statistician, 5(3), 115–145. https://doi.org/10.2307/2986645 Guarnieri, F. & da Silva, G. P. (2022). A spatial interaction model of vote dispersion. Political Geography, 98, 102709. https://doi.org/10.1016/j.polgeo.2022.102709 H. Ayuntamiento de Ciudad Juárez. (2024). Plan Municipal de Desarrollo (PMD) 2021-2024. Hamad, P. A., & Ali, Y. A. (2024). A Geographical Analysis of the Parties’ Votes in the Electoral Districts of Kurdistan Region for the 2021 Election of the Council of Representatives of Iraq. Journal of University of Raparin, 11(1), 713–747. https://doi.org/10.26750/Vol(11).No(1).Paper29 Hernández, C. (2018). Campañas electorales presidenciales pragmáticas en México 2018. Política y comunicación. Revista Mexicana de Ciencias Políticas y Sociales, 64(235), 327–352. https://doi.org/10.22201/fcpys.2448492xe.2019.235.67468 Hernández, V. (2015). Análisis geoespacial de las elecciones presidenciales en México, 2012. Eure, 41(122). https://doi.org/10.4067/S0250-71612015000100009 Hernández, V. & De Haro, L. (2020). Geografía de la participación electoral y diferenciación socioespacial en Ciudad Juárez, Chihuahua (México). Geopolítica(s). Revista de estudios sobre espacio y poder, 11(1), 145–172. https://doi.org/10.5209/geop.63962 Hollander, M., Wolfe, D. A. & Chicken, E. (2014). Nonparametric Statistical Methods. John Wiley & Sons, Inc. Iglesias-Pascual, R., Benassi, F., & Paloma, V. (2022). A Spatial Approach to the Study of the Electoral Resurgence of the Extreme Right in Southern Spain. Spatial Demography, 10(1), 117–141. https://doi.org/10.1007/s40980-022-00105-1 INE. (2025). Sistema de Consulta de la Estadística de Elecciones. Instituto Nacional Electoral. https://siceen21.ine.mx/home Johnston, R., & Pattie, C. (2006). Putting Voters in their Place. Geography and Elections in Great Britain. Oxford University Press Inc. Kovalcsik, T., & Nzimande, N. P. (2019). Theories of the voting behaviour in the context of electoral and urban geography. Belvedere Meridionale, 31(4), 207–220. https://doi.org/10.14232/belv.2019.4.15 Kruskal, W. H. & Wallis, W. A. (1952). Use of Ranks in One-Criterion Variance Analysis. Journal of the American Statistical Association, 47(260), 583–621. https://doi.org/10.1080/01621459.1952.10483441 Lee, H.-C. & Repkine, A. (2022). A Spatial Analysis of the Voting Patterns in the South Korean General Elections of 2016. Social Sciences, 11(9), 389. https://doi.org/10.3390/socsci11090389 Lizama, G. (2012). Geografía electoral del abstencionismo en los municipios de México (1994-2009). Espacialidades, 2(2), 22–51. Mitra, A. (2020). Electoral David vs Goliath: How does the Spatial Concentration of Electors affect District-based Elections? 1–16. https://www.readkong.com/page/electoral-david-vs-goliath-how-does-the-spatial-3126859 Navarrete, J. P. (2024). Elecciones 2024. Análisis Plural, 6 (3), 1-15. https://doi.org/10.31391/ap.vi6.112 Nohlen, D. (1996). Sistemas electorales y reforma electoral. Quid Juris, 7–58. Razali, N. M. & Wah, Y. B. (2011). Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling test. Journal of Statistical Modeling and Analytcs, 2(2), 21–33. Sanguin, A. L. (1980). Geografía Política. Barcelona: OIKOS-TAU SA. Shapiro, S. S. & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3–4), 591–611. https://doi.org/10.1093/biomet/52.3-4.591 Silva, G. P. da, & Davidian, A. (2013). Identification of areas of vote concentration: evidences from Brazil. Brazilian Political Science Review, 7(2), 141–155. https://doi.org/10.1590/S1981-38212013000200006 Skachkov, V. S. (2020 Problems of study of electoral geography of Mexicoin the XXI Century. Bulletin of the Moscow State Regional University (Geographical Environment and Living Systems), 2, 44–51. https://doi.org/10.18384/2712-7621-2020-2-44-51 Sonnleitner, W. (2017a). Rastreando las dinámicas territoriales de la fragmentación partidista en México (1991-2015). América Latina Hoy, 75, 23–54. https://doi.org/10.14201/alh2017752354 Sonnleitner, W. (2017b). Variedades del voto: Hacia una sociología plural del sufragio particular, Estudios Sociológicos de El Colegio de México, 35(104), 429–448. https://doi.org/10.24201/es.2017v35n104.1536 Sonnleitner, W. (2020). La reconfiguración territorial de las fuerzas políticas mexicanas: geografía de la fragmentación, el colapso y la recomposición del sistema de partidos (2012-2018). Foro Internacional, 451–500. https://doi.org/10.24201/fi.v60i2.2731 Stephens, M. A. (1974). EDF Statistics for Goodness of Fit and Some Comparisons. Journal of the American Statistical Association, 69(347), 730–737. https://doi.org/10.1080/01621459.1974.10480196 Truglia, F. G. & Zeli, A. (2020). Spatial analysis of economic and social determinants of vote: the case of the European Parliament and constitutional referendum votes in Italy. Italian Political Science Review/Rivista Italiana di Scienza Politica, 50(2), 173–190. https://doi.org/10.1017/ipo.2019.29 Unwin, A. (1996). Geary’s Contiguity Ratio. The Economic and Social Review, 27(2), 145–159. Verma, A. (2022). Electoral Geography: Approaches to Study Voting Behavior. RESEARCH REVIEW International Journal of Multidisciplinary, 7(3), 68–73. https://doi.org/10.31305/rrijm.2022.v07.i03.012 Vilalta, C. J. (2008). ¿Se pueden predecir geográficamente los resultados electorales? Una aplicación del análisis de clusters y outliers espaciales / Can Electoral Results Be Geographically Predicted? A Spatial Clusters and Outliers Analysis. Estudios Demográficos y Urbanos, 23(3), 571–613. https://doi.org/10.24201/edu.v23i3.1322 Wiedemann, A. (2023). Replication Data for: Redistributive Politics Under Spatial Inequality (Version V1) [Data set]. Harvard Dataverse. https://doi.org/doi:10.7910/DVN/CXAVEF Wilcoxon, F. (1945). Individual Comparisons by Ranking Methods. Biometrics Bulletin, 1(6), 80. https://doi.org/10.2307/3001968; http://erevistas.uacj.mx/ojs/index.php/noesis/article/view/6853

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