scholarly journals Place and City: Toward Urban Intelligence

2018 ◽  
Vol 7 (9) ◽  
pp. 346 ◽  
Author(s):  
Albert Acedo ◽  
Marco Painho ◽  
Sven Casteleyn ◽  
Stéphane Roche
Keyword(s):  
Social Capital ◽  
Sense Of Place ◽  
Spatial Data ◽  
Spatial Clustering ◽  
Natural Habitat ◽  
Spatial Relationship ◽  
Point Of View ◽  
Individual Level ◽  
Place Studies ◽  
Spatial Dimensions

Place, as a concept, is subject to a lively, ongoing discussion involving different disciplines. However, most of these discussions approach the issue without a geographic perspective, which is the natural habitat of a place. This study contributes to this discourse through the exploratory examination of urban intelligence utilizing the geographical relationship between sense of place and social capital at the collective and individual level. Using spatial data collected through a web map-based survey, we perform an exhaustive examination of the spatial relationship between sense of place and social capital. We found a significant association between sense of place and social capital from a spatial point of view. Sense of place and social capital spatial dimensions obtain a non-disjoint relationship for approximately half of the participants and a spatial clustering when they are aggregated. This research offers a new exploratory perspective for place studies in the context of cities, and simultaneously attempts to depict a platial–social network based on sense of place and social capital, which cities currently lack.

scholarly journals Is there no “I” in team? Potential bias in key informant interviews when asking individuals to represent a collective perspective

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0261452
Author(s):  
Whitney Fleming ◽  
Brittany King ◽  
Kerrick Robinson ◽  
Eric Wade ◽  
Brian Erickson ◽  
...  
Keyword(s):  
Sense Of Place ◽  
Language Use ◽  
Interesting Case ◽  
Point Of View ◽  
Personal Perspective ◽  
Potential Bias ◽  
Structured Interviews ◽  
Individual Level ◽  
Key Informant ◽  
The Individual

This paper sought to understand the extent to which, and how individuals use personal or collective language when asked to articulate sense of place from a collective perspective. Understanding a collective sense of place could illuminate place-based connections in natural resource industries, where it is as groups or as institutions that organizations interact with the environment rather than as individuals. While there are well known methods for collecting information about sense of place at the individual level, there is a gap in understanding the best method to collect information at a collective level. We examined the use of key-informant interviews as a method to understand collective sense of place. In Bocas del Toro, Panama, ecotourism and environmentally based organizations are becoming more prolific due to abundant natural resources, making it an interesting case study for understanding sense of place from an organizational perspective. The use of personal and collective language is examined though in-depth semi-structured interviews from 15 environmentally-oriented organizations with a total of 17 interviews. This study specifically examined whether and how key informants, when prompted to speak for their organization, spoke collectively, reflecting a collective perspective versus their own. Methods included both quantitative analysis of personal versus collective language use frequency, and qualitative examinations of how individuals used personal versus collective language. Our results indicated no difference in the frequency with which individuals use personal versus collective language. We found that how individuals situated their perspectives into an organization reflects a complex personal and collective point of view reflecting five themes of personal versus collective language use: 1) sole personal perspective, 2) sole collective perspective, 3) distinction between collective and personal perspective; 4) organization perspective with insertion of “I think”; and 5) personal and collective perspective about organization and greater community. Our research identifies a previously undiscussed potential bias of key informant interviews. These findings have implications for how researchers approach collecting information beyond the individual level.

History of Tour de France from the Geographical Point of View

2013 ◽  
Vol 22 (3-4) ◽  
pp. 255-277 ◽  
Author(s):  
Vladimír Bačík ◽  
Michal Klobučník
Keyword(s):  
Point Of View ◽  
The Past ◽  
Advanced Technologies ◽  
The World ◽  
Spatial Dimensions ◽  
Tour De France ◽  
Wide Circle ◽  
History Of ◽  
Expert Community ◽  
Geographical Point

Abstract The Tour de France, a three week bicycle race has a unique place in the world of sports. The 100th edition of the event took place in 2013. In the past of 110 years of its history, people noticed unique stories and duels in particular periods, celebrities that became legends that the world of sports will never forget. Also many places where the races unfolded made history in the Tour de France. In this article we tried to point out the spatial context of this event using advanced technologies for distribution of historical facts over the Internet. The Introduction briefly displays the attendance of a particular stage based on a regional point of view. The main topic deals with selected historical aspects of difficult ascents which every year decide the winner of Tour de France, and also attract fans from all over the world. In the final stage of the research, the distribution of results on the website available to a wide circle of fans of this sports event played a very significant part (www.tdfrance.eu). Using advanced methods and procedures we have tried to capture the historical and spatial dimensions of Tour de France in its general form and thus offering a new view of this unique sports event not only to the expert community, but for the general public as well.

scholarly journals Spatial analysis for political scientists

2021 ◽  
pp. 1-17
Author(s):  
Jessica Di Salvatore ◽  
Andrea Ruggeri
Keyword(s):  
Comparative Politics ◽  
Spatial Data ◽  
Spatial Clustering ◽  
Statistical Tests ◽  
Spatial Regression ◽  
Spatial Models ◽  
Building Blocks ◽  
Spatial Relationships ◽  
Electoral Studies ◽  
Data Points

Abstract How does space matter in our analyses? How can we evaluate diffusion of phenomena or interdependence among units? How biased can our analysis be if we do not consider spatial relationships? All the above questions are critical theoretical and empirical issues for political scientists belonging to several subfields from Electoral Studies to Comparative Politics, and also for International Relations. In this special issue on methods, our paper introduces political scientists to conceptualizing interdependence between units and how to empirically model these interdependencies using spatial regression. First, the paper presents the building blocks of any feature of spatial data (points, polygons, and raster) and the task of georeferencing. Second, the paper discusses what a spatial matrix (W) is, its varieties and the assumptions we make when choosing one. Third, the paper introduces how to investigate spatial clustering through visualizations (e.g. maps) as well as statistical tests (e.g. Moran's index). Fourth and finally, the paper explains how to model spatial relationships that are of substantive interest to some of our research questions. We conclude by inviting researchers to carefully consider space in their analysis and to reflect on the need, or the lack thereof, to use spatial models.

scholarly journals Explainable Spatial Clustering: Leveraging Spatial Data in Radiation Oncology

2020 ◽  
Author(s):  
Andrew Wentzel ◽  
Guadalupe Canahuate ◽  
Lisanne V. van Dijk ◽  
Abdallah S.R. Mohamed ◽  
C. David Fuller ◽  
...  
Keyword(s):  
Spatial Data ◽  
Radiation Oncology ◽  
Spatial Clustering

Spatial clustering analysis of green economy based on knowledge graph

2021 ◽  
pp. 1-10
Author(s):  
Shiyuan Zhou ◽  
Xiaoqin Yang ◽  
Qianli Chang
Keyword(s):  
Spatial Data ◽  
Clustering Analysis ◽  
Spatial Clustering ◽  
Evaluation Model ◽  
Principal Component ◽  
Green Economy ◽  
Membership Degree ◽  
Two Dimensional ◽  
Dimensional Graph ◽  
Improved Algorithm

By organically combining principal component analysis, spatial autocorrelation algorithm and two-dimensional graph theory clustering algorithm, the comprehensive evaluation model of regional green economy is explored and established. Based on the evaluation index system of regional green economy, this paper evaluates the development of regional green economy comprehensively by using principal component analysis, and evaluates the competitive advantage of green economy and analyzes the spatial autocorrelation based on the evaluation results. Finally, the green economy and local index score as observed values, by using the method of two-dimensional graph clustering analysis of spatial clustering. In view of the fuzzy k –modes cluster membership degree measure method without considering the defects of the spatial distribution of object, double the distance and density measurement of measure method is introduced into the fuzzy algorithm of k –modes, thus in a more reasonable way to update the membership degree of the object. Vote, MUSH-ROOM and ZOO data sets in UCI machine learning library were used for testing, and the F value of the improved algorithm was better than that of the previous one, indicating that the improved algorithm had good clustering effect. Finally, the improved algorithm is applied to the spatial data collected from Baidu Map to cluster, and a good clustering result is obtained, which shows the feasibility and effectiveness of the algorithm applied to spatial data. Results show that the development of green economy using the analysis method of combining quantitative analysis and qualitative analysis, explores the connotation of green economy with space evaluation model is feasible, small make up for the qualitative analysis of the green economy in the past, can objective system to reflect the regional green economic development level, will help policy makers scientific formulating regional economic development strategy, green integrated development of regional green economy from the macroscopic Angle, the development of network system.

scholarly journals From Substitutive to Supplementary: Institutional Interplay between Public and Occupational Sickness Benefits in Finland, 1947-2016

2021 ◽  
Vol 23 (1) ◽  
pp. 62-80
Author(s):  
Laura Järvi
Keyword(s):  
Welfare State ◽  
Institutional Development ◽  
Point Of View ◽  
Sickness Benefit ◽  
Individual Level ◽  
The Public ◽  
Blue Collar Workers ◽  
Sickness Benefits ◽  
Over Time ◽  
Benefit System

In the context of the Finnish welfare state, this article examines the role of occupational welfare in the interplay between public and occupational sickness benefits from 1947 to 2016, to analyse how the two sickness benefits have interacted over time and the role occupational welfare has played in sickness provision. Previous research has noted that occupational benefits may support or compensate for the much-debated declining welfare state. Hence, it is important to acquire greater knowledge about the public-occupational interplay. The study uses in-depth individual-level analysis from a retrospective point of view, which has been rare in previous research, and examines the public-occupational interplay in the Finnish sickness benefit system from the first national collective agreements to 2016. Based on the reforms made to the public system, the article identifies and utilises six different phases of the Finnish sickness allowance system in the main analysis. The institutional development of sickness provision is investigated by analysing the compensation rate and benefit period, using metalworkers as a representative example of blue-collar workers. The results indicate that occupational benefits are strongly institutionalised in the Finnish sickness benefit system. The interplay between statutory and occupational sickness benefits has taken different forms over time, and occupational benefits have been re-negotiated as the statutory system has been reformed. The article provides valuable information on the historical development and relevance of occupational welfare, in terms of not only understanding its significance for individuals but also comprehending the logic of the interplay in the public-private mix of welfare provision.

scholarly journals The “Dark Side” Effects of Social Capital on Harmful Drinking among Chinese Community Residents: A Multilevel Study

2018 ◽  
Vol 15 (10) ◽  
pp. 2249 ◽  
Author(s):  
Xin Nie ◽  
Yongkai Zhu ◽  
Hua Fu ◽  
Junming Dai ◽  
Junling Gao
Keyword(s):  
Social Capital ◽  
Social Participation ◽  
Odds Ratio ◽  
Dark Side ◽  
Chinese Community ◽  
Harmful Drinking ◽  
Individual Level ◽  
Social Organizations ◽  
Multilevel Study ◽  
Community Residents

Background: To determine the effects of social capital on harmful drinking (HD) among Chinese community residents using a multilevel study. Methods: A cross-sectional study conducted from 2017–2018. In total, 13,610 participants were randomly interviewed from 29 districts of 3 cities in China with a multi-stage sampling procedure. Social capital, including social cohesion, membership in social organizations, and frequency of social participation, were assessed using validated scales. HD was assessed using the CAGE four-item questionnaire. Multilevel models were developed to determine whether social capital was related to HD when socioeconomic and demographic covariates were controlled. Results: In general, the prevalence of HD was 8.18%, and more specifically, 13.77% for men and 2.74% for women. After controlling for covariates and stratifying by gender, compared to residents in the low individual-level membership of social organizations, we found that the odds ratio (OR) for HD was 1.30 with a 95% confidence interval (CI) of 1.07–1.56 among men and 1.95 (95% CI: 1.29–2.97) among women. Compared to residents in the low individual-level frequency of social participation groups, the odds ratio of HD among women was 1.58 (95% CI: 1.10–2.26). There was no association between district-level social capital and HD. Conclusions: A high level of social capital may promote HD among the residents of Chinese neighborhoods. Intervention to modify social capital under the Chinese drinking culture may help reduce HD.

scholarly journals Does workplace social capital protect against long-term sickness absence? Linking workplace aggregated social capital to sickness absence registry data

2017 ◽  
Vol 46 (3) ◽  
pp. 290-296 ◽  
Author(s):  
Anne-Sophie K. Hansen ◽  
Ida E. H. Madsen ◽  
Sannie Vester Thorsen ◽  
Ole Melkevik ◽  
Jakob Bue Bjørner ◽  
...  
Keyword(s):  
Social Capital ◽  
Private Sector ◽  
Sickness Absence ◽  
Collective Good ◽  
Standard Deviation Increase ◽  
Individual Level ◽  
The Individual ◽  
Adjusted Model ◽  
Workplace Social Capital

Aims: Most previous prospective studies have examined workplace social capital as a resource of the individual. However, literature suggests that social capital is a collective good. In the present study we examined whether a high level of workplace aggregated social capital (WASC) predicts a decreased risk of individual-level long-term sickness absence (LTSA) in Danish private sector employees. Methods: A sample of 2043 employees (aged 18–64 years, 38.5% women) from 260 Danish private-sector companies filled in a questionnaire on workplace social capital and covariates. WASC was calculated by assigning the company-averaged social capital score to all employees of each company. We derived LTSA, defined as sickness absence of more than three weeks, from a national register. We examined if WASC predicted employee LTSA using multilevel survival analyses, while excluding participants with LTSA in the three months preceding baseline. Results: We found no statistically significant association in any of the analyses. The hazard ratio for LTSA in the fully adjusted model was 0.93 (95% CI 0.77–1.13) per one standard deviation increase in WASC. When using WASC as a categorical exposure we found a statistically non-significant tendency towards a decreased risk of LTSA in employees with medium WASC (fully adjusted model: HR 0.78 (95% CI 0.48–1.27)). Post hoc analyses with workplace social capital as a resource of the individual showed similar results. Conclusions: WASC did not predict LTSA in this sample of Danish private-sector employees.

Tree-ART2 Learning Model for Spatial Clustering in Second Dimension

2014 ◽  
Vol 543-547 ◽  
pp. 1934-1938
Author(s):  
Ming Xiao
Keyword(s):  
Network Model ◽  
Spatial Data ◽  
Data Clustering ◽  
Clustering Algorithm ◽  
Spatial Clustering ◽  
Adaptive Resonance Theory ◽  
Spatial Distance ◽  
Resonance Theory ◽  
Adaptive Resonance ◽  
Vector Module

For a clustering algorithm in two-dimension spatial data, the Adaptive Resonance Theory exists not only the shortcomings of pattern drift and vector module of information missing, but also difficultly adapts to spatial data clustering which is irregular distribution. A Tree-ART2 network model was proposed based on the above situation. It retains the memory of old model which maintains the constraint of spatial distance by learning and adjusting LTM pattern and amplitude information of vector. Meanwhile, introducing tree structure to the model can reduce the subjective requirement of vigilance parameter and decrease the occurrence of pattern mixing. It is showed that TART2 network has higher plasticity and adaptability through compared experiments.

Social Capital and Self-Perceived Health in Lone Mothers: A Multilevel Cross-Sectional Study across Europe

2021 ◽  
pp. 0192513X2199416
Author(s):  
Sara Trujillo-Alemán ◽  
Åsa Tjulin ◽  
Glòria Pérez ◽  
Emma Hagqvist
Keyword(s):  
Social Capital ◽  
Family Policy ◽  
Social Activity ◽  
Perceived Health ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Policy Model ◽  
Individual Level ◽  
Country Level ◽  
Lone Mothers

This study aimed to explore the distribution of social capital and its relation to self-perceived health in lone mothers across Europe. Data were drawn from the European Social Survey Round 5. The sample was restricted to women (15–64 years), not cohabiting with a partner, and with children (≤ 18 years) living in the household. Social capital was measured using variables, representing both structural (political engagement, social support, and social activity) and cognitive (generalized trust, institutionalized trust, reciprocity, and a feeling of safety) components. Individual-level measurements: age, educational attainment, employment status, income level, and household economy. Country-level measurements: family policy model and collective social capital. A multilevel analysis was conducted. The results revealed cross-country variance in the level of lone mothers’ social capital. After adjustment for individual-level and country-level measurements, only reciprocity and a feeling of safety were related to good self-perceived health among lone mothers in Europe.

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