游客对肢体残障人士出游的态度差异——人口统计学特征影响的混合研究

基于出游障碍理论框架,于2019—2020年问卷调查308名游客和开放式访谈13位肢残人士,运用混合研究方法,识别游客对肢残人士出游的态度,并分析游客人口统计学特征对肢残人士出游态度的影响差异。结果表明：（1）游客认同社会公众态度是阻碍肢残人士出游的最重要因素,大部分游客对接触肢残游客不存在顾虑,但介意一同出游。（2）游客对肢残人士出游的具体态度包括出游意义认同、出游环境改善、其他人群的友好态度、交流愿望与自信以及拒绝心理。（3）年龄对游客态度影响最大,表现为负向影响交流愿望与自信、正向影响拒绝心理;游客受教育程度、职业、性别分别对交流愿望与自信、拒绝心理、出游环境改善的态度有显著影响。访谈资料有效解释了大部分定量分析结果,但在受教育程度对游客态度的影响方面,得出的结果与定量分析相反。     

江西省耕地转移驱动机理

构建涵盖农业生产、耕地向建设用地转移和耕地向林/草地转移的江西省土地用途转移驱动机理模型,采用分段估计逐步增加解释变量的方法测度了人口、社会、经济、区位和自然因素等驱动土地用途转移的机理。研究表明,人口规模是江西省土地用途转移的重要驱动力,社会经济因素在短时间内起决定性作用,各种驱动力以各种方式组合来增强或者减弱其对区域土地用途转移的作用效果。其中,农业人口规模及生产投入要素是影响江西省农业生产的主要因素;人口规模、平原面积比例及土地管理政策是江西省耕地向建设用地转移过程的重要解释变量;农业人口比重、地形坡度、粮食产量及非农产业是江西省耕地向林/草地转移过程的重要影响因素,并揭示了解释了江西省在众多驱动力作用下土地用途转移规律。     

我国东中西部碳排放量影响因素面板数据研究

为促进省域低碳经济发展,以碳排放量为研究对象,采用5个解释变量建立面板数据模型.研究发现:经济增长和产业结构是影响东中部碳排放量的2个最重要变量,影响系数东部依次为0.602,0.544,中部依次为1.441,0.407,其次是人均收入水平、人口增长和能源价格:在西部,人均收入水平和产业结构是影响其碳排放量的2个最重要变量,影响系数分别为0.967,0.788,其次是人口增长、能源价格和经济增长状况:能源价格影响度从东到西依次提高,特别是人均收入对西部碳排放量影响度远远超过东部:因地制宜,对于东、中部地区政府要重视优化经济增长方式和调整其产业结构,对于西部更应重视调整人均收入政策及加强能源价格控制.面板单位根检验我国东中西部各变量均存在一阶单整,面板协整检验省域碳排放量与人们收入水平、经济增长水平、产业结构、能源价格和人口增长之间存在长期稳定内生经济关系.     

公众环境意向与亲环境行为:社会信任的调节效应研究

破解生态环境保护领域“知行脱节”困境,是加快构建生态环境保护社会行动体系需要解决的首要问题。基于结构方程模型和跨区域大样本数据,研究社会信任对环境意向与亲环境行为关联度的调节效应。结果表明:公众对日常环境污染具有较高危机感和鲜明态度,这种危机感和态度促使公众愿意为环境保护做出某种程度的付出;公众愿意为环境保护做出付出的意向越强烈,实施相应的亲环境行为的可能性就越高。但这种关联度受到社会信任水平的调节,公众持有社会信任水平越高,其付出意向与亲环境行为关联度就越强,实施亲环境行为的可能性就越大;反之,实施亲环境行为的可能性就越小。     

风景区毗邻社区居民旅游感知和态度的差异及机制研究——以黄山市汤口镇为例

居民感知和态度是居民对旅游发展最直观的评价。因异质性因素的影响,旅游地居民的感知和态度会存在差异。已有研究成果表明,在较大空间尺度内,距离因素是居民感知和态度差异的重要解释变量。为了研究小尺度空间内居民感知和态度的异质性因素,以毗邻黄山风景区的4个社区为例进行实证研究。通过问卷调查和深入访谈发现,社区居民在旅游发展期望,对旅游经济、生活环境和社会文化积极和消极影响的感知均存在一定的差异性。从区位、社区和风景区3个方面梳理毗邻社区旅游发展历程发现,距离风景区的相对区位、社区组织介入资源开发和协调利益分配的能力,以及风景区治理模式的变迁共同影响了社区旅游发展和居民旅游收益,导致了居民旅游感知和态度的差异。研究结论显示,相对于区位条件和风景区治理模式等外在因素,毗邻社区需要充分发挥社区组织的能动作用,促进社区与风景区协调发展。     

转型期广州市城市居民住房产权分异研究

利用社会-人口统计学研究方法,以问卷调查结果为基础,从自置房和租赁房、资助房和商品房两个层面,分析住房产权分异影响因素,研究发现社会经济特征变量与组织变量对住房产权分异都有显著影响,尤其是组织变量对资助房与商品房产权分异的影响更显著.家庭社会经济特征,如户主年龄、婚姻状况、家庭规模和家庭收入对产权分异的影响基本与西方类似.国有单位和工龄长的职工,享受资助房的机会相对较多.目前的住房制度改革集中在住房的私有化和大规模的商品房开发建设上,应更加关注新形势下住房分配的不平等.     

周庄古镇创造性破坏与地方身份转化

地方身份通过内外部政治经济力量交互作用,成为当地社会关系的历史纹理,是利益相关者意识形态的反映。以周庄为案例地,借助创造性破坏模型深入分析古镇地方身份转化。研究发现：周庄满足该模型的3 个主要变量。与西方企业家主导模式不同,中国政府对旅游的推动作用是强大的,不仅履行决策制定者和投资者的职能,而且为象征资本的创造、社会资本的延伸和文化资本的维护做出贡献;伴随着游客数量的增加和动机的多样化,商业化景观迅速蔓延,不断冲击古镇遗产景观身份;居民对旅游发展的态度经历了积极—消极—积极的回归过程。从文化霸权与表征、游客凝视、人口置换与社会身份复杂性等角度对周庄古镇地方身份转化进行理论解释,认为地方身份是利益相关者之间相互"谈判"和妥协的产物,表征主流意识形态;为适应游客凝视,利益相关者以东拼西凑的形式改造古镇地方身份;人口置换的结果增加了"新周庄人"社会身份的复杂性,由此带来社会关系破碎、社会认同下降、地方感丧失等问题,导致周庄地方身份转化。     

交互作用视角下人口流动性与住房类型对城市入室盗窃空间格局的影响

已有研究发现社区住房类型对城市入室盗窃的空间格局有重要影响,但鲜有学者探讨位于不同人口流动程度社区环境中的不同住房对入室盗窃影响的差异。本研究以中国东南沿海城市ZG市为例,基于日常活动和社会失序等理论,以社区为分析单元,利用入室盗窃警情数据、第六次人口普查数据和兴趣点数据（Point of Interest, POI）,运用空间滞后负二项回归方法,分析人口流动性与住房类型的交互作用对入室盗窃空间格局的影响。结果表明：人口流动性高的社区入室盗窃率较高;自建住房比例对入室盗窃率有显著的正向影响,原公有住房比例和商品房比例则呈显著的抑制作用;交互变量的结果发现,人口流动性与不同类型住房变量的交互作用存在差异,其中,人口流动性与自建住房、经济适用房、原公有住房的交互变量对入室盗窃的发生具有显著的促进作用,而与商品房的交互对入室盗窃的影响并不显著。说明在探讨不同类型住房与入室盗窃的关系时,应重视其所在社区的人口流动程度的影响。     

老龄化社会背景下对我国城市规划的思考

从我国老龄化的社会背景出发,分析了城市“人口红利”优势的弱化、老龄产业的兴起与发展、老年住房供需矛盾突出、老年社会角色的延续与转换等相关性特征.认为我国城市管理者或规划师应前瞻性地认识中国老龄化社会发展趋势,对城市规划从城市发展策略、用地布局、交通组织、社区规划、公众参与等过程作出应对性的调整,制定适合老年主体人群的城市规划体系,以维护社会各阶层的合法利益,体现出城市规划的公共政策性.     

经济发展梯度影响下的江苏农用地土壤重金属含量分布格局

根据江苏省农用地22个标准样地的7种重金属元素含量测定结果,应用TWINSPAN分类、CCA排序的多元统计方法,对江苏农用地耕作层土壤重金属元素含量格局和影响因子进行了定量分析.研究结果表明,江苏耕作层土壤重金属元素含量整体特征具有明显的沿经济发展梯度(苏南-苏中-苏北)的递减格局.空间位置、人类活动强度、土壤理化性质是控制梯度分布格局重要的环境因素,通过变量分离,空间变量解释的部分占21.5%,人为活动变量解释部分占17.9%,理化性质变量解释部分占17.5%,三组变量总解释量占56.9%,不能解释部分占43.1%.人类活动与空间位置因素一起可以综合反映江苏经济发展的空间梯度,其占了总解释量的69.2%,经济发展梯度对农用地重金属元素含量有着深刻的影响.     

Dynamics of educational development in the Chhattisgarh region,India

"The aim of this paper is to analyse the spatial patterns of the level of educational development along with the decennial change in the literacy rate in the Chhattisgarh region of Madhya Pradesh State [India]. Eleven variables...have been considered to find out the index of educational development in the tahsils [divisions] of the region. The eighty two tahsils...are grouped into four categories...on the basis of decennial growth rate in literacy during 1981-91 and the level of educational development...."     

Temporal stability of model parameters in crime rate analysis: An empirical examination

Two common practices in modeling of crime when crime data is available for multiple years are using single-year crime data corresponding to census data and taking the average of crime rate (or count) over multiple years. Current theoretical and empirical literature provides little, if any, rationale in support of either practice. Averaging multiple years is purported to reduce heterogeneity and minimize the measurement error in the year-to-year emergence of crime. However, it is unclear how useful the analysis of averaged and smoothed data is for revealing the relationship between crimes and socio-demographic and economic characteristics of every single year. In order to more clearly understand these two approaches, this paper applies a seemingly unrelated regression model to assess the temporal stability of model parameters. The model accounts for spatial autocorrelation among crime rates and social disorganization variables at the block group level.     

Multilevel built environment features and individual odds of overweight and obesity in Utah

Based on the data from the Behavioral Risk Factor Surveillance System (BRFSS) in 2007, 2009 and 2011 in Utah, this research uses multilevel modeling (MLM) to examine the associations between neighborhood built environments and individual odds of overweight and obesity after controlling for individual risk factors. The BRFSS data include information on 21,961 individuals geocoded to zip code areas. Individual variables include BMI (body mass index) and socio-demographic attributes such as age, gender, race, marital status, education attainment, employment status, and whether an individual smokes. Neighborhood built environment factors measured at both zip code and county levels include street connectivity, walk score, distance to parks, and food environment. Two additional neighborhood variables, namely the poverty rate and urbanicity, are also included as control variables. MLM results show that at the zip code level, poverty rate and distance to parks are significant and negative covariates of the odds of overweight and obesity; and at the county level, food environment is the sole significant factor with stronger fast food presence linked to higher odds of overweight and obesity. These findings suggest that obesity risk factors lie in multiple neighborhood levels and built environment features need to be defined at a neighborhood size relevant to residents' activity space.     

Ecological Worldview as the Central Component of Environmental Concern: Clarifying the Role of the NEP

This study examines whether an ecological worldview—operationalized by the New Ecological Paradigm (NEP) Scale--serves as the source of coherence of Environmental Concern (EC). Using data on four samples from the 1992 Gallup “Health of the Planet” Survey and the 2003 and 2010 Chinese General Social Surveys, we found that in all samples not only is the NEP the most powerful predictor of EC, but it also mediates the effects of socio-demographic variables on EC as hypothesized. The results confirm that the NEP is the source of coherence of EC, making it a meaningful construct.     

Assessing environmental inequalities in the city of Santiago (Chile) with a hierarchical multiscale approach

Environmental inequalities are a common characteristic of urban areas. Environmental inequality is the unequal spatial distribution of environmental risks and goods among social groups. As environmental inequalities are inherently a spatial matter the choice of scale is essential for correctly understanding inequality issues and for designing proper and effective mitigation policies. However, the potential effects of scale of analysis on inequalities results have largely been underestimated in the assessment of environmental inequalities, leading to contradictory results from different studies. In this study we assess the patterns of environmental inequalities and associated scale issues in the city of Santiago (Chile) using a hierarchical multiscale approach. Our approach focuses on the analysis of spatial relationships between three environmental (i.e., surface temperature, air pollution, vegetation cover) and two socio-demographic variables (i.e., household wealth, population density) on multiple grain sizes and extents. We used census data, remote sensing data, and air pollution monitoring stations to generate raster layers at five grain sizes and five nested extents. We tested for inequalities through Pearson correlation analysis resulting in a total of 1530 assessed relationships. Our results show that environmental inequalities are a prevalent phenomenon in the city of Santiago, but the details of these inequalities are highly scale dependent. Changing the grain size and extent of analysis do not only affect the strength of relationships between socio-demographic and environmental variables, but also the spatial distribution of environmental inequalities across the urban landscape. Therefore, due to the scale-dependence of assessment results, researchers and decision-makers should be extremely careful when interpreting their findings and translating them into policy making. If the scale dependency of environmental inequalities is not taken into account, policy interventions may be largely ineffective because the scale at which interventions are designed may not match the scale at which inequalities are generated.     

ANALYSIS OF QUALITATIVE DATA USING GLIM: TWO EXAMPLES BASED ON SHOPPING SURVEY DATA

We recommend use of the widely available computer package GLIM to analyze relationships involving categorical, or qualitative, variables. The package is flexible and fairly simple to use and readily produces data plots as well as information on parameter estimates and residual values. In order to explain how to fit log-linear and logistic-linear models using GLIM, we give two examples based on sample survey data from grocery shoppers in Oxford, England. In the first, we examine relationships between a categorical response to an attitude statement and categorical explanatory variables using the log-linear model and, in the second, relationships between use and a mixture of continuous and categorical explanatory variables using the logistic-linear (logit) model.     

Who moves into, out of and within London?

Summary Eight variables from the 1991 Census 2% Sample of Anonymised Records are used to classify Greater London's population into ten socio-demographic groups. This provides the basis for examining differences between 'types of people' in the extent to which they changed address in the year before the Census and whether they moved into, out of or within London.     

COMMUNICATIONS FROM READERS

We recommend use of the widely available computer package GLIM to analyze relationships involving categorical, or qualitative, variables. The package is flexible and fairly simple to use and readily produces data plots as well as information on parameter estimates and residual values. In order to explain how to fit log-linear and logistic-linear models using GLIM, we give two examples based on sample survey data from grocery shoppers in Oxford, England. In the first, we examine relationships between a categorical response to an attitude statement and categorical explanatory variables using the log-linear model and, in the second, relationships between use and a mixture of continuous and categorical explanatory variables using the logistic-linear (logit) model.     

Student Attitudes and the Impact of GIS on Thinking Skills and Motivation

Abstract

The value of GIS within school curricula seems well perceived but ill-substantiated. This paper discusses the role of GIS in the development of higher order thinking skills and in motivating student learning. It then reports on attitudinal surveys undertaken before and after student exposure to GIS-related tasks. The tasks formed part of four subjects within three year levels. Data were collected from 109 students from two schools. Individual survey items were evaluated using a t-test for paired means and a two-tailed test for significance. Weighted average responses for the five constructs being surveyed were calculated. Attitudinal improvements were found in three of these: perceived usefulness of computers, perceived control of computers and behavioural attitude to computers. The weighted average declined for the remaining two constructs: attitude to subject and affective attitude toward computers. These data suggest that GIS influences student ability to utilise higher level thinking skills within a context of enhanced relevance.     

Mapping the Urban Debtscape: The Geography of Household Debt in Canadian Cities

Abstract

Vulnerability resulting from debt is part and parcel of the risk society and a salient characteristic of current neoliberal times under financialized global capitalism. Rising indebtedness increases the susceptibility of homeowners to housing and labor market restructuring, and if the degree of leverage is very high, can threaten the solvency, living standards, and social stability of local communities. However, very little is understood regarding how levels of household indebtedness are spatially distributed within or across cities, and how private debt maps onto the geography of race, class, housing, urban form, and other social variables, especially outside of the United States. It remains unknown whether and how higher and unsustainable levels of indebtedness might be associated with urban growth, decline, suburbanization, gentrification, immigration, racialization, and/or greying. This article examines the spatial distribution of household debt in Canadian cities at multiple scales of analysis. It analyzes how levels of household debt relate to a number of key socio-demographic and housing variables from the census, including those related to changes occurring over the 2000s. It simultaneously models the geography of debt at the metropolitan and neighborhood scales using multi-level hierarchical linear modeling methods, and in doing so, it identifies some key drivers and correlates of household debt and the scales at which they operate. The article concludes by discussing the implications of the empirical findings for understanding the role of the emerging urban debtscape in the restructuring of the social geography of the city.