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Perception of Vulnerable Ultra-Poor Women on Climate Change Impacts and Local Adaptation in a High Flood Prone Area of Bangladesh

TL;DR: In this paper, the authors explored different perceptions of climate change and its local adaptation options among ultra-poor vulnerable women, particularly in highly vulnerable flood-prone regions of Bangladesh, and identified some major adaptation options such as plinth raising, livestock rearing, homestead gardening, seasonal migration, and using indigenous knowledge.
Abstract: The contextual and risk perception of climate change plays a critical role in an individual’s decision-making process. It could also help people to respond appropriately to the consequences of global climate change and eventually take necessary adaptation actions. However, the perceptions of climate change are often gendered and vary among men and women. Therefore, this study explores different perceptions of climate change and its local adaptation options among ultra-poor vulnerable women, particularly in highly vulnerable flood-prone regions of Bangladesh. The research followed an empirical research methodology to collect primary and secondary information using qualitative and quantitative research tools. The study findings reveal that climate change perceptions at the individual level are relatively low (63%). Still, they have been observing significant changes in various climatic variables over the past 30 years. Moreover, this study identified some major adaptation options such as plinth raising (100%), livestock rearing (100%), homestead gardening (82%), seasonal migration (82%), and using indigenous knowledge (69%), and so on to tackle the adverse impacts of climate change-induced extreme events including flooding at the local level. For implementing these adaptation measures, the respondents spent a significant amount of financial resources from individual sources in the study area. Structural Equation Modeling (SEM) is used in addition to the statistical analyses to understand any connections between the climate change perceptions and other variables associated with the community under study. The SEM result shows that climate change will be a long–term problem, which offers a strong predictor in this model, considering standardized regression weight β= 0.56. It means, despite inadequate knowledge on climate change of the respondent’s, climate change is occurring and becoming the worst factor limiting cultural, economic, and environmental development in the study area.

Summary (3 min read)

Introduction

  • It could also help people to respond appropriately to the consequences of global climate change and eventually take necessary adaptation actions.
  • Even though anthropogenic global warming is one of the biggest global threats to human existence, risk assessments of global climate change vary considerably from one individual to another (Hine et al., 2013; van der Linden, 2017).
  • Lack of access and ownership of land and wealth makes women vulnerable to economically challenged situations triggered by environmental stresses.
  • This study has been carried out to understand the perception and impact of climate change among ultra-poor vulnerable women and find out local adaptation options, particularly in the highly susceptible flood-prone areas like the Sirajganj district of Bangladesh.

2.1 Study Area

  • Chowhali Upazila under the Sirajganj district is one of the most vulnerable flood-affected areas in Bangladesh.
  • This study was conducted in seven unions of the Upazila; most of the unions are flood affected.
  • Hassan et al., (2016) conducted a remote sensing study using three multi-date Landsat imageries.
  • Location map of the study area, also known as Future 1.

2.1 Data Collection and Analysis

  • Both quantitative and qualitative approaches were applied to explore the perception of different vulnerabilities of vulnerable women due to climate change in the study area.
  • The survey was collected responses from 200 climate-vulnerable ultra-poor women in 7 unions of the Upazila.
  • (1) suffer daily food insecurity, (2) no land or less than 0.15 acres, (3) deplorable housing condition, (4) womenheaded household, and (5) no active male income earner, also known as These specific criteria were.
  • Moreover, some significant descriptive statistics such as mean value, total number, range, regression, percentage, and standard deviation were produced to analyze the surveyed data.
  • Structural Equation Modeling (SEM) is a widely used statistical modeling tool in social science research where a combination of path analysis, factor analysis, and multiple regressions is prevalent to delve into the different latent and apparent relationship of variables (Hox et al., 1998).

3.1 Socio-economic Profiles

  • Only female respondents were counted for the survey.
  • Women can be the best way to emphasize adaptation to climate change impacts (UNICEF, 2016).
  • Only 25% of the respondents completed primary education.
  • About 34% of respondents had marginal households, and 19% had small families.

3.2 Perceptions of Climate Change

  • The study shows that only 37% of the respondents were concerned with climate change's general concept .
  • The rest of the 63% never heard about climate change.
  • When the respondents familiar with the topic asked about the source of the knowledge of climate change, a significant number (55%) replied NGO as a source, followed by T.V. (26%) and radio (19%).
  • This study reveals that direct education, training, or communication positively impact educating vulnerable poor women on climate change-related issues.
  • In addition to this finding, most of the respondents did not have proper scientific explanations and climate change results.

3.3 Major Changes in Climate

  • Figure 3 demonstrates the main climatic changes over the last 30 years noticed by the respondents.
  • All the respondents observed irregular and less rainfall in the study area, while 93% said rain was not in time.
  • The overall climate change scenario in the study area is exposed to less rainfall and increasing temperature trend during the past 30 years.
  • 7% of the respondents replied about a more extended summer period, while 87.5% talked about a shorter winter period.
  • Half of the interviewees witnessed the increasing natural disasters during the last 30 years.

3.4 Major Changes in the Ecosystem and Environment

  • The impacts of climate variability and change in the study are severe, shown in Figure 3.
  • Based on this figure, the development of the overall ecosystem and environmental sustainability is in danger that may affect the socio-economic and agriculture areas also.
  • All of the respondents perceived drought conditions during the dry season.
  • Approximately 81% of respondents witnessed less water in the river and wetlands.
  • Heavy rainfall is another negative consequence during the last 30 years, referred by 25% of respondents.

3.5 Major Changes in Human Well-Being

  • Climate change and its consequences not only have effects on the environment but also human well-being.
  • 81% of the respondents suffered internal migration due to poverty and family demands .
  • About 43.75% of the respondents got lower work hours due to adverse impacts of climate change, and a similar percentage mentioned mental stress in their daily life.
  • Major adverse impacts on human well-being, also known as Figure 5.
  • Among the vulnerable groups, children are the most affected, 87% of the total people affected.

3.6 Major Changes in Agriculture

  • As an agricultural country, the effects of climate change on agriculture are one of the most significant concerns.
  • All the respondents agreed to the point that climate change has an impact on the loss of soil fertility and increased crop production cost .
  • All interviewees also opined that plant or agriculture lands go underwater during flooding and sometimes covered with sand.
  • The next significant adverse impacts are crop failure, which was opined by 87.5% of the respondents.
  • One-fourth of the interviewees mentioned that the food crisis exists in the study area.

3.7 Local Adaptation to Climate Change

  • Figure 8 shows the current adaptation options for climatic impacts.
  • Other options include the change of livelihood, taking a loan, using indigenous knowledge, crop diversification, selling household assets, mortgaging land, a loan from NGO, tree plantation, and seasonal fishing.
  • People affected by the climate change consequences have tried many ways of adapting by spending their own money.
  • Present climate change adaptation options, also known as Figure 8.

3.8 Investment for Local Adaptations

  • It means, despite inadequate expertise on climate change of the respondent’s, climate change is happening and becoming the worst factor delaying cultural, economic, and environmental development in the study area.
  • These events also contributed to increased waterborne diseases and depletion of natural resources and eventually impacted local population livelihoods, including women at risk.
  • Mujaffor (2011) argued that growing awareness and dissemination on climate change issues through different media channels can play a crucial role in improving sustainable development at the community level.
  • In national climate change policies, the programs should essentially include gender perspective adaptation policies.. .

5. Conclusion

  • This study explores the different perceptions of climate change and its adaptation options from ultra-poor women in the study area using a set of quantitative and a few KIIs data.
  • As a result, they had to invest in implementing these adaptation processes ranging from $20-45 at the household level.
  • From the SEM results, climate change is real and happening in this study area.
  • The main limitation of this study was the low sample size and not using other secondary information.
  • Local government, NGOs, and other development actors may use these findings for preparing any development initiatives in the study area related to the climate change and environmental studies.

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Perception of Vulnerable Ultra-Poor Women on Climate
Change Impacts and Local Adaptation in a High Flood
Prone Area of Bangladesh
Md. Shareful Hassan
Center for Environmental Change Studies and Management,
Dhaka, Bangladesh
Syed Mahmud-ul-Islam
Institute of Environmental Science, University of Rajshahi,
Rajshahi, Bangladesh
Mohammad Mahbubur Rahman
Department of Sociology, Lancaster University,
Bowland North, UK
Saeid Eslamian
Department of Water Engineering, Collage of Agriculture, Isfahan University of
Technology,
Isfahan 84156 83111, Iran
ABSTRACT: The contextual and risk perception of climate change plays a critical role in an individual’s decision-
making process. It could also help people to respond appropriately to the consequences of global climate change and
eventually take necessary adaptation actions. However, the perceptions of climate change are often gendered and
vary among men and women. Therefore, this study explores different perceptions of climate change and its local
adaptation options among ultra-poor vulnerable women, particularly in highly vulnerable flood-prone regions of
Bangladesh. The research followed an empirical research methodology to collect primary and secondary information
using qualitative and quantitative research tools. The study findings reveal that climate change perceptions at the
individual level are relatively low (63%). Still, they have been observing significant changes in various climatic
variables over the past 30 years. Moreover, this study identified some major adaptation options such as plinth raising
(100%), livestock rearing (100%), homestead gardening (82%), seasonal migration (82%), and using indigenous
knowledge (69%), and so on to tackle the adverse impacts of climate change-induced extreme events including
flooding at the local level. For implementing these adaptation measures, the respondents spent a significant amount
of financial resources from individual sources in the study area. Structural Equation Modeling (SEM) is used in
addition to the statistical analyses to understand any connections between the climate change perceptions and other
variables associated with the community under study. The SEM result shows that climate change will be a long
term problem, which offers a strong predictor in this model, considering standardized regression weight β= 0.56. It
means, despite inadequate knowledge on climate change of the respondent’s, climate change is occurring and
becoming the worst factor limiting cultural, economic, and environmental development in the study area.
KEYWORDS: Climate change, vulnerable women, perception, adaptation, Bangladesh, high flood
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021
© 2021 by the author(s). Distributed under a Creative Commons CC BY license.
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021 doi:10.20944/preprints202105.0475.v1
© 2021 by the author(s). Distributed under a Creative Commons CC BY license.

1. Introduction
Climate change poses considerable uncertainty concerning both the intensity and the temporal or
spatial pattern of its impacts on the individual's decision-making process (Woods et al., 2017).
Research findings on how people act under high uncertainty conditions suggest that individuals
consistently overlook the risk of a disaster affecting them, and these have profound implications
(Grothmann and Patt, 2005). Contextual perceptions of risk are unconsciously chosen ideologies
that facilitate an individual's way of life, as explained by cultural cognition theory (Lacroix and
Gifford, 2018). Every individual has beliefs about how the world should be. Because some risks
promote particular ideas more than others, individuals "selectively...attribute or deny the
evidence of risk in patterns that match values that they exchange with each other" (Kahan et al.,
2011). For instance, considering that egalitarians do not like unfair social disparities (Kahan,
2008; Kahan and Braman, 2003); and given that most people believe climate change risks to
others around the world to be higher than the risks to themselves, it follows that egalitarians are
more likely to be involved with climate change because it endangers their view of a socially fair
and equitable society (Lacroix and Gifford, 2018).
Risk perception is a mental construct (Sjöberg, 2000). Human perception is exceptional since it
makes it possible to distinguish between the nature of concrete, immediate threats, such as
climate change, and the subjective perception of those threats (Rosa, 2003). For instance, even
though anthropogenic global warming is one of the biggest global threats to human existence,
risk assessments of global climate change vary considerably from one individual to another
(Hine et al., 2013; van der Linden, 2017). Moreover, there is a substantial cross-cultural
difference in the intensity of combined public concern and a general eagerness to address the
problem. In the United Kingdom, Australia, and most of mainland Europe, climate change, for
instance, has always been seen as a "substantial" problem. On the other hand, it has traditionally
been gained lower attention in countries such as the United States, China, and Russia (van der
Linden, 2017). Of that kind, prejudices can skew perceptions of risk, a key mechanism for
motivating adaptive behavior. For example, studies of flood insurance purchases have shown
that, even if the flood damage is severe, people prefer to disregard the possibility of flood risks
when they have a low flood probability scenario (Woods et al., 2017).
The differential consequences of climate change on men and women emerge from diverse roles
in society, how these roles are boosted or diminished by other aspects of injustice, perceived
risks, and the nature of disaster response (Field et al., 2014). Vulnerability study results on
climate change showed that the factors of men's and women's vulnerability and adaptation
capacity were gender-sensitive and mediated by cultural, socio-economic, and political structures
and processes (Carr and Thompson, 2014). Moreover, several socio-demographic variables,
including gender, race, education, access to the property, and social networks, can be used to
label the most vulnerable (Baptiste and Kinlocke, 2016). In general, women have often been
perceived by their increasing dependence upon natural resources and increased poverty among
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021 Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021 doi:10.20944/preprints202105.0475.v1

the most vulnerable victims of climate change (Arora-Jonsson, 2011; Mainlay and Tan, 2012;
Lawson et al., 2020). Poor women are the most vulnerable and most affected by climate change,
especially in developing countries (Swai et al., 2012). Bangladesh, one of the developing
countries from the global south, is at a high risk of frequent climatic disasters such as flooding,
cyclone, riverbank erosion, sea-level rise, etc. Though natural disasters affect all population
groups, some researchers have found gender-specific exposure and disaster effects. This
vulnerability is more triggered by other social problems such as sexual integrity and poverty,
mainly confronted by women and adolescent girls, making them further insecure and shocked
(Azad et al., 2013). Therefore, women here are more susceptible than men to climate-related
impacts because of their social condition, cultural norms, lack of access to and control over
resources, and lack of participation in decision-making processes (Khan et al., 2010). Among
other South Asian countries, the geographical context has made Bangladesh more vulnerable to
seasonal flooding, causing tremendous loss of human life and property. An average of 844,000
million cubic meters of water runs across the country during the rainy season (MayOctober)
through the three most important river systems- the Ganges, the Brahmaputra, and the Meghna.
As a low-lying country where almost eighty percent of the landmass covers floodplain, it
exposes to repeated floods (Dewan, 2015). The marginal and disadvantaged group of people,
including the poor, physically challenged, and ethnic minorities, are the forefront victims of the
aftereffect of any natural disasters, including floods. More precisely, among these groups of the
marginal community, women, children, and adults' susceptibility are of the highest degree.
However, individuals could play a significant role in responding to a changing climate and
disaster situation (CCC, 2009).
For decades social scientists and environmental sociologists have researched gender dynamics in
scientific understanding and the ecological problem. The results are a combination of robust
designs as well as unresolved consequences. These consist of a multidisciplinary study exploring
public opinion on climate change or global warming, a vital science-based environmental issue
full of political controversy and moral concern (McCright, 2010). Most previous studies (ex.
Pearse, 2017; Swai et al., 2012; McCright, 2010) concentrated on gender relations of climate
change, exploring vulnerability and adaptation in different contexts, and knowledge and social
action targeting both males and females. However, there is hardly ever any study (ex. Selm et al.,
2019; Lawson et al., 2020) that focuses principally on women or women-headed households and
their perspectives of basic understanding of climate change and knowledge of its adaptation and
response options. Besides, less work is being done on a systematic public opinion analysis that
explores the conceptual dimension of gender relations with climate change attitudes and beliefs.
Conversely, researchers generally include gender as a statistical control in multivariate models
and then only explain this variable's effectiveness in passingoften with little or no empirical
discourse (McCright, 2010). A noticeable number of researches (ex. Huq et al., 1999; Alam et
al., 2017; Rahaman et al., 2019; Rahaman and Rahman, 2020) have assessed the implications of
climate change in different sectors in Bangladesh. In contrast, the study on climate change
impacts on ultra-poor women and their risk perceptions is less explored. Instead, most studies
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021 Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021 doi:10.20944/preprints202105.0475.v1

consider multiple groups of vulnerable populations in their studies (ex. Haq and Ahmed, 2017).
Thus, this study will examine the risk perceptions of these less explored population groups,
particularly women.
Sirajganj district is historically known as one of the most vulnerable areas in Bangladesh that
face frequent seasonal flooding and havoc visits. Sirajganj is inundated nearly each year, with the
most drastic floods occurring in 1949, 1956, 1961, 1962, 1966, 1968, 1974, 1979, 1987, 1988,
1996, 1998, 2002, 2004, 2007, 2008, 2014, 2016, and 2019 (Ali et al., 2019). Khan et al. (2010)
have shown that the intensity of extreme climatic events such as flooding, impact, and response
depends on the socio-economic conditions amongst a vulnerable group of people, including the
poor, ultra-poor, and wealthy class. Both the hard and soft adaptation knowledge is crucial to
coping with the distractions caused by extreme disasters. A local community, affected by the
unexpected conditions due to climate change, tries different alternatives and strategies to cope
with it. Affected people adopt livelihood strategies using their indigenous knowledge and coping
mechanisms. Among the strategies, diversification of livelihoods and cropping patterns, such as
introducing floating gardening, poultry and duck rearing, cage aquaculture, building sea wave
protection walls, pond or canal excavation, and dam construction, are remarkable, and mostly
these are hard adaptation measures (Anik et al., 2012).
Women and women-headed households in rural areas like the Sirajganj district, in general, are
more likely to experience more poverty than the urban areas and, at the same time, more
vulnerable than men to various natural disasters, including flooding. Moreover, widowed women
are supposed to be weaker in social safety and empowerment than those with a well-earning
husband or rich and good-family-network. Women also have less socio-economic power
compare to men. In village areas, men go to cities searching for jobs, leaving women in their
home village. Women in the town often look after their families and work harder to feed their
children or dependent. Thus, reasonably women are more likely than men to be experienced with
local disasters in flood-prone areas. Therefore, climate change impacts affect vastly ultra-poor
women in remote and rural flood-prone regions. The activities of women in the affected area are
also noteworthy. Women are involved in cultivation, and post-harvest works along with men
(NAPA, 2009). They are also taking part in tailoring, fishnet making, cattle farming, poultry, and
handicrafts making. In rural communities, women overwhelmingly undertake the labor of
collecting food, water, and energy resources for cooking that increase collection time. Women's
activities contribute to their families' existence by ensuring food security (Nasreen, 2008; 2012).
However, lack of access and ownership of land and wealth makes women vulnerable to
economically challenged situations triggered by environmental stresses. Thus, knowledge and
understanding of climate change and its impacts and response could be an essential tool for
promoting soft adaptation strategies and improving their coping capacities in such rural flood-
prone areas. This knowledge will also help them in keeping their families safe during the disaster
period.
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021 Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021 doi:10.20944/preprints202105.0475.v1

This study has been carried out to understand the perception and impact of climate change
among ultra-poor vulnerable women and find out local adaptation options, particularly in the
highly susceptible flood-prone areas like the Sirajganj district of Bangladesh. Along with other
statistical analyses, Structural Equation Modeling (SEM) has been used to understand any links
between climate change perceptions and other associated variables. Based on this study's
background literature materials, this SEM will be a noble work as none of these studies
addressed this issue in the Bangladeshi context. Therefore, this study will provide a proper
guideline on using SEM for climate change studies in Bangladesh, particularly flood-prone areas.
2. Methods
2.1 Study Area
Chowhali Upazila under the Sirajganj district is one of the most vulnerable flood-affected areas
in Bangladesh. This study was conducted in seven unions of the Upazila; most of the unions are
flood affected. This Upazila lies between 24°01'N and 24°17'N latitudes and between 89°41'E
and 89°59'E longitudes. The entire Upazila covers 21,039 hectares area (Figure 1). The Jamuna
River passes through the Upazila that brings ample bank erosion, causing the displacement of
many human settlements. Hassan et al., (2016) conducted a remote sensing study using three
multi-date Landsat imageries. It estimated that about 1340-hectare areas had been eroded
between 1989 and 2015 in different parts of the entire study area. This zone is mainly selected as
the study area due to its high vulnerability to flood, river erosion, and climate change's adverse
impacts.
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021 Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 May 2021 doi:10.20944/preprints202105.0475.v1

References
More filters
Journal ArticleDOI
TL;DR: In this paper, a socio-cognitive model of private proactive adaptation to climate change (MPPACC) is proposed, which separates out the psychological steps to taking action in response to perception, and allows one to see where the most important bottlenecks occur.
Abstract: Adaptation has emerged as an important area of research and assessment among climate change scientists. Most scholarly work has identified resource constraints as being the most significant determinants of adaptation. However, empirical research on adaptation has so far mostly not addressed the importance of measurable and alterable psychological factors in determining adaptation. Drawing from the literature in psychology and behavioural economics, we develop a socio-cognitive Model of Private Proactive Adaptation to Climate Change (MPPACC). MPPACC separates out the psychological steps to taking action in response to perception, and allows one to see where the most important bottlenecks occur—including risk perception and perceived adaptive capacity, a factor largely neglected in previous climate change research. We then examine two case studies—one from urban Germany and one from rural Zimbabwe—to explore the validity of MPPACC to explaining adaptation. In the German study, we find that MPPACC provides better statistical power than traditional socio-economic models. In the Zimbabwean case study, we find a qualitative match between MPPACC and adaptive behaviour. Finally, we discuss the important implications of our findings both on vulnerability and adaptation assessments, and on efforts to promote adaptation through outside intervention.

1,543 citations


"Perception of Vulnerable Ultra-Poor..." refers background in this paper

  • ...Research findings on how people act under high uncertainty conditions suggest that individuals consistently overlook the risk of a disaster affecting them, and these have profound implications (Grothmann and Patt, 2005)....

    [...]

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TL;DR: This article found that cultural cognition shapes individuals' beliefs about the existence of scientific consensus and the process by which they form such beliefs, relating to climate change, the disposal of nuclear wastes, and the effect of permitting concealed possession of handguns.
Abstract: Why do members of the public disagree – sharply and persistently – about facts on which expert scientists largely agree? We designed a study to test a distinctive explanation: the cultural cognition of scientific consensus. The ‘cultural cognition of risk’ refers to the tendency of individuals to form risk perceptions that are congenial to their values. The study presents both correlational and experimental evidence confirming that cultural cognition shapes individuals’ beliefs about the existence of scientific consensus, and the process by which they form such beliefs, relating to climate change, the disposal of nuclear wastes, and the effect of permitting concealed possession of handguns. The implications of this dynamic for science communication and public policy‐making are discussed.

1,113 citations

Journal ArticleDOI
TL;DR: This article found evidence that cultural cognition shapes individuals' beliefs about the existence of scientific consensus and the process by which they form such beliefs, relating to climate change, the disposal of nuclear wastes, and the effect of permitting concealed possession of handguns.
Abstract: Why do members of the public disagree - sharply and persistently - about facts on which expert scientists largely agree? We designed a study to test a distinctive explanation: the cultural cognition of scientific consensus. The "cultural cognition of risk" refers to the tendency of individuals to form risk perceptions that are congenial to their values. The study presents both correlational and experimental evidence confirming that cultural cognition shapes individuals' beliefs about the existence of scientific consensus, and the process by which they form such beliefs, relating to climate change, the disposal of nuclear wastes, and the effect of permitting concealed possession of handguns. The implications of this dynamic for science communication and public policy-making are discussed.

978 citations


"Perception of Vulnerable Ultra-Poor..." refers background in this paper

  • ...Because some risks promote particular ideas more than others, individuals "selectively...attribute or deny the evidence of risk in patterns that match values that they exchange with each other" (Kahan et al., 2011)....

    [...]

Journal ArticleDOI
TL;DR: The authors found that women express slightly greater concern about climate change than do men, and this gender divide is not accounted for by differences in key values and beliefs or in the social roles that men and women differentially perform in society.
Abstract: This study tests theoretical arguments about gender differences in scientific knowledge and environmental concern using 8 years of Gallup data on climate change knowledge and concern in the US general public. Contrary to expectations from scientific literacy research, women convey greater assessed scientific knowledge of climate change than do men. Consistent with much existing sociology of science research, women underestimate their climate change knowledge more than do men. Also, women express slightly greater concern about climate change than do men, and this gender divide is not accounted for by differences in key values and beliefs or in the social roles that men and women differentially perform in society. Modest yet enduring gender differences on climate change knowledge and concern within the US general public suggest several avenues for future research, which are explored in the conclusion.

639 citations


"Perception of Vulnerable Ultra-Poor..." refers background in this paper

  • ...These consist of a multidisciplinary study exploring public opinion on climate change or global warming, a vital science-based environmental issue full of political controversy and moral concern (McCright, 2010)....

    [...]

  • ...Conversely, researchers generally include gender as a statistical control in multivariate models and then only explain this variable's effectiveness in passing—often with little or no empirical discourse (McCright, 2010)....

    [...]

  • ...Pearse, 2017; Swai et al., 2012; McCright, 2010) concentrated on gender relations of climate change, exploring vulnerability and adaptation in different contexts, and knowledge and social action targeting both males and females....

    [...]

01 Jan 1998
TL;DR: The basic elements of a structural equation model are presented, the estimation technique is introduced, and some problems concerning the assessment and improvement of the model fit, and model extensions to multigroup problems including factor means are discussed.
Abstract: This article presents a short and non-technical introduction to Structural Equation Modeling or SEM. SEM is a powerful technique that can combine complex path models with latent variables (factors). Using SEM, researchers can specify confirmatory factor analysis models, regression models, and complex path models. We present the basic elements of a structural equation model, introduce the estimation technique, which is most often maximum Likelihood (ML), and discuss some problems concerning the assessment and improvement of the model fit, and model extensions to multigroup problems including factor means. Finally, we discuss some of the software, and list useful handbooks and Internet sites. What is Structural Equation Modeling? Structural Equation Modeling, or SEM, is a very general statistical modeling technique, which is widely used in the behavioral sciences. It can be viewed as a combination of factor analysis and regression or path analysis. The interest in SEM is often on theoretical constructs, which are represented by the latent factors. The relationships between the theoretical constructs are represented by regression or path coefficients between the factors. The structural equation model implies a structure for the covariances between the observed variables, which provides the alternative name covariance structure modeling. However, the model can be extended to include means of observed variables or factors in the model, which makes covariance structure modeling a less accurate name. Many researchers will simply think of these models as ‘Lisrel-models,’ which is also less accurate. LISREL is an abbreviation of LInear Structural RELations, and the name used by Joreskog for one of the first and most popular SEM programs. Nowadays structural equation models need not be linear, and the possibilities of SEM extend well beyond the original Lisrel program. Browne (1993), for instance, discusses the possibility to fit nonlinear curves. Structural equation modeling provides a very general and convenient framework for statistical analysis that includes several traditional multivariate procedures, for example factor analysis, regression analysis, discriminant analysis, and canonical correlation, as special cases. Structural equation models are often visualized by a graphical path diagram. The statistical model is usually represented in a set of matrix equations. In the early seventies, when this technique was first introduced in social and behavioral research, the software usually required setups that specify the model in terms of these matrices. Thus, researchers had to distill the matrix representation from the path diagram, and provide the software with a series of matrices for the different sets of 1 Note: The authors thank Alexander Vazsonyi and three anonymous reviewers for their comments on a previous version. We thank Annemarie Meijer for her permission to use the quality of sleep data. Introduction Structural Equation Modeling 2 parameters, such as factor loadings and regression coefficients. A recent development is software that allows the researchers to specify the model directly as a path diagram. This works well with simple problems, but may get tedious with more complicated models. For that reason, current SEM software still supports the commandor matrix-style model specifications too. This review provides a brief and non-technical review of the basic issues involved in SEM, including issues of estimation, model fit, and statistical assumptions. We include a list of available software, introductory books, and useful Internet resources. Examples of SEM-Models In this section, we set the stage by discussing examples of a confirmatory factor analysis, regression analysis, and a general structural equation model with latent variables. Structural equation modeling has its roots in path analysis, which was invented by the geneticist Sewall Wright (Wright, 1921). It is still customary to start a SEM analysis by drawing a path diagram. A path diagram consists of boxes and circles, which are connected by arrows. In Wright’s notation, observed (or measured) variables are represented by a rectangle or square box, and latent (or unmeasured) factors by a circle or ellipse. Single headed arrows or ‘paths’ are used to define causal relationships in the model, with the variable at the tail of the arrow causing the variable at the point. Double headed arrows indicate covariances or correlations, without a causal interpretation. Statistically, the single headed arrows or paths represent regression coefficients, and double-headed arrows covariances. Extensions of this notation have been developed to represent variances and means (cf. McArdle, 1996). The first example in Figure 1 is a representation of a confirmatory factor analysis model, with six observed variables and

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Frequently Asked Questions (2)
Q1. What are the contributions mentioned in the paper "Perception of vulnerable ultra-poor women on climate change impacts and local adaptation in a high flood prone area of bangladesh" ?

Therefore, this study explores different perceptions of climate change and its local adaptation options among ultra-poor vulnerable women, particularly in highly vulnerable flood-prone regions of Bangladesh. The research followed an empirical research methodology to collect primary and secondary information using qualitative and quantitative research tools. The study findings reveal that climate change perceptions at the individual level are relatively low ( 63 % ). Moreover, this study identified some major adaptation options such as plinth raising ( 100 % ), livestock rearing ( 100 % ), homestead gardening ( 82 % ), seasonal migration ( 82 % ), and using indigenous knowledge ( 69 % ), and so on to tackle the adverse impacts of climate change-induced extreme events including flooding at the local level. For implementing these adaptation measures, the respondents spent a significant amount of financial resources from individual sources in the study area. It means, despite inadequate knowledge on climate change of the respondent ’ s, climate change is occurring and becoming the worst factor limiting cultural, economic, and environmental development in the study area. 

Further research on this similar issue may have a robust sample size with mixed-method data collection and analysis. However, this study can be used as technical guidance for analyzing the similar ecosystem data in Bangladesh and other areas.