Jun 4, 2018 | Demography, Postdoc, Poverty & Equity, Women in Science
©Nandita Saikia
By Nandita Saikia, Postdoctoral Research Scholar at IIASA
Being an author of a research article on excess female deaths in India in Lancet Global Health, one of the world’s most prestigious and high impact factor public health journals, today I questioned myself: Did I dream of reaching here when I was a little school going girl in the early nineties in a remote village in North East India?
I am the fourth daughter of five. In a country like India, where the status of women is undoubtedly poorer than men even now, and newspapers are often filled with heinous crimes against women, you may be able to imagine what it meant being a fourth daughter. Out of five sisters, three of us were born because my parents wanted a son. My mother, who barely completed her school education, did not want more than two children irrespective of sex, but was pressurized by the extended family to go for a boy after a third daughter and six years of repeated abortions.
I was told in my childhood that I was the most unwanted child in the family. I was a daughter, terribly underweight until age 11, and had much darker skin than my elder sisters and most people from our area, who have fairer skin than average in India. At my birth, my father, a college dropout farmer, was away in a relative’s house and when he heard about the arrival of another girl, he postponed his return trip.
This is a real story, but just one of those still happening in India. The fact that the girls of India are unwanted was observed from the days of early 20th century when it was written in the 1901 census:
“There is no doubt that, as a rule, she [a girl] receives less attention than would be bestowed upon a son. She is less warmly clad, … She is probably not so well fed as a boy would be, and when ill, her parents are not likely to make the same strenuous efforts to ensure her recovery.”
Regrettably, our current study shows that negligence against “India’s daughter” continues to this day.
Discrimination against the girl child can be divided in two categories: before birth and after birth. Modern techniques now allow sex-selective abortion. Despite strong laws, more than 63 million women are estimated to be ‘missing’ in India and the discrimination occurs at all levels of society.
Our present study deals with gender discrimination after birth. We found that over 200,000 girls under the age of five died in 2005 in India as a result of negligence. We found that excess female mortality was present in more than 90% of districts, but the four largest states of North India (Uttar Pradesh, Bihar, Rajasthan, and Madhya Pradesh) accounted for two thirds of India’s total number.
I have to tell you that I was luckier than most girls. Although I was an unwanted child in our extended family, to my mother, this underweight, dark-skinned, little girl was as cute as the previous ones! She gave her best care to her daughter, and she named her “Rani” meaning “Queen” in Assamese. I am still called by this name in my family and in my village.
When I grew up, I asked her several times about her motive for calling me Rani. She always replied: “You were so ugly, the thinnest one with dark skin, I named you as “Rani” because I wanted everyone to have a positive image before seeing you! Also, it is the name of my favorite teacher in high school and she was also a very thin but bright lady!”
The positive conversations with my mother played a crucial role to my desire to have my own identity, and influenced greatly my positive image of myself and my belief that I could do something worthwhile with my life. Much later, when I started my PhD at International Institute for Population Sciences (IIPS), Mumbai, I was surprised to learn that in Maharashtra, one of the wealthiest states of India, second or third daughters are not even given a name, but instead are called ‘Nakusha’, meaning unwanted.
My parents were passionate about educating their daughters, even with their limited means. My father, who was disappointed at my birth, left no stone unturned for my education! By the time I completed secondary school, our village, as well as neighboring villages, congratulated me during the Bihu celebration (the biggest local gathering) for my good performance in school exams. My parents were proud of me by that time; yet, for some strange reason, they always felt themselves weaker than our neighbors who had sons.
Now, people from our village are proud of me not just because I teach in India’s premier university, or that I take several overseas trips in a year, but because they realize that daughters can equally bring renown to their village; daughters can be married off without a dowry; daughters can equally provide old age care to their parents; daughters too can buy property! Due to this attitude and lower fertility levels, many couples now don’t prefer sons over daughters. In a village of 200 households, there are 33 couples that have either one or two daughters, yet did not keep trying for sons. In my own extended family, no one chooses to have more than two children irrespective of their sex. The situation has changed in my village, but not everywhere.
What is the solution of this deep-rooted social menace? We cannot expect a simple solution. However, my own story convinces me that education can be a game changer, but not necessarily academic degrees. I mean a system by which girls realize their own worth and their capability that they can be economically and socially empowered and can drive their own lives. With the help of education, I made myself from an “unwanted” to a wanted daughter!
The purpose of sharing my story is neither self-promotion nor to gain sympathy, rather to inspire millions of girls, who face numerous challenges in everyday life just because of their gender, and doubt their capability, just like I did in my school days. They can make a difference if they want! Nothing can stop them!
Jan 15, 2018 | Data and Methods, Demography
By Dilek Yildiz, Wittgenstein Center for Demography and Global Human Capital (IIASA, VID/ÖAW and WU), Vienna Institute of Demography, Austrian Academy of Sciences, International Institute for Applied Systems Analysis
Social media offers a promising source of data for social science research that could provide insights into attitudes, behavior, social linkages and interactions between individuals. As of the third quarter of 2017, Twitter alone had on average 330 million active users per month. The magnitude and the richness of this data attract social scientists working in many different fields with topics studied ranging from extracting quantitative measures such as migration and unemployment, to more qualitative work such as looking at the footprint of second demographic transition (i.e., the shift from high to low fertility) and gender revolution. Although, the use of social media data for scientific research has increased rapidly in recent years, several questions remain unanswered. In a recent publication with Jo Munson, Agnese Vitali and Ramine Tinati from the University of Southampton, and Jennifer Holland from Erasmus University, Rotterdam, we investigated to what extent findings obtained with social media data are generalizable to broader populations, and what constitutes best practice for estimating demographic information from Twitter data.
A key issue when using this data source is that a sample selected from a social media platform differs from a sample used in standard statistical analysis. Usually, a sample is randomly selected according to a survey design so that information gathered from this sample can be used to make inferences about a general population (e.g., people living in Austria). However, despite the huge number of users, the information gathered from Twitter and the estimates produced are subject to bias due to its non-random, non-representative nature. Consistent with previous research conducted in the United States, we found that Twitter users are more likely than the general population to be young and male, and that Twitter penetration is highest in urban areas. In addition, the demographic characteristics of users, such as age and gender, are not always readily available. Consequently, despite its potential, deriving the demographic characteristics of social media users and dealing with the non-random, non-representative populations from which they are drawn represent challenges for social scientists.
Although previous research has explored methods for conducting demographic research using non-representative internet data, few studies mention or account for the bias and measurement error inherent in social media data. To fill this gap, we investigated best practice for estimating demographic information from Twitter users, and then attempted to reduce selection bias by calibrating the non-representative sample of Twitter users with a more reliable source.
Exemplar of CrowdFlower task © Jo Munson.
We gathered information from 979,992 geo-located Tweets sent by 22,356 unique users in South-East England and estimated their demographic characteristics using the crowd-sourcing platform CrowdFlower and the image-recognition software Face++. Our results show that CrowdFlower estimates age more accurately than Face++, while both tools are highly reliable for estimating the sex of Twitter users.
To evaluate and reduce the selection bias, we ran a series of models and calibrated the non-representative sample of Twitter users with mid-year population estimates for South-East England from the UK Office of National Statistics. We then corrected the bias in age-, sex-, and location-specific population counts. This bias correction exercise shows promise for unbiased inference when using social media data and can be used to further reduce selection bias by including other sociodemographic variables of social media users such as ethnicity. By extending the modeling framework slightly to include an additional variable, which is only available through social media data, it is also possible to make unbiased inferences for broader populations by, for example, extracting the variable of interest from Tweets via text mining. Lastly, our methodology lends itself for use in the calculation of sample weights for Twitter users or Tweets. This means that a Twitter sample can be treated as an individual-level dataset for micro-level analysis (e.g., for measuring associations between variables obtained from Twitter data).
Reference:
Yildiz, D., Munson, J., Vitali, A., Tinati, R. and Holland, J.A. (2017). Using Twitter data for demographic research, Demographic Research, 37 (46): 1477-1514. doi: 10.4054/DemRes.2017.37.46
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Aug 16, 2017 | Climate Change, Young Scientists
By Parul Tewari, IIASA Science Communication Fellow 2017
As climate change warms up the planet, it is the Arctic where the effects are most pronounced. According to scientific reports, the Arctic is warming twice as fast in comparison to the rest of the world. That in itself is a cause for concern. However, as the region increasingly becomes ice-free in summer, making shipping and other activities possible, another threat looms large. That of an oil spill.
©AllanHokins I Flickr
While it can never be good news, an oil spill in the Arctic could be particularly dangerous because of its sensitive ecosystem and harsh climatic conditions, which make a cleanup next to impossible. With an increase in maritime traffic and an interest in the untapped petroleum reserves of the Arctic, the likelihood of an oil spill increases significantly.
Maisa Nevalainen, as part of the 2017 Young Scientists Summer Program (YSSP), is working to assess the extent of the risk posed by oil spills in the Arctic marine areas.
“That the Arctic is perhaps the last place on the planet which hasn’t yet been destroyed or changed drastically due to human activity, should be reason enough to tread with utmost caution,” says Nevalainen
Although the controversial 1989 Exxon Valdez spill in Prince William Sound was quite close to the Arctic Circle, so far no major spills have occurred in the region. However, that also means that there is no data and little to no understanding of the uncertainties related to such accidents in the region.
For instance, one of the significant impacts of an oil spill would be on the varied marine species living in the region, likely with consequences carrying far in to the future. Because of the cold and ice, oil decomposes very slowly in the region, so an accident involving oil spill would mean that the oil could remain in the ice for decades to come.
Thick-billed Murre come together to breed in Svalbard, Norway. Nevalainen’s study so far suggests that birds are most likely to die of an oil spill as compared to other animals. © AllanHopkins I Flickr
Yet, researchers don’t know how vulnerable Arctic species would be to a spill, and which species would be affected more than others. Nevalainen, as part of her study at IIASA will come up with an index-based approach for estimating the vulnerability (an animal’s probability of coming into contact with oil) and sensitivity (probability of dying because of oiling) of key Arctic functional groups of similar species in the face of an oil spill.
“The way a species uses ice will affect what will happen to them if an oil spill were to happen,” says Nevalainen. Moreover, oil tends to concentrate in the openings in ice and this is where many species like to live, she adds.
During the summer season, some islands in the region become breeding grounds for birds and other marine species both from within the Arctic and those that travel thousands of miles from other parts of the world. If these species or their young are exposed to an oil spill, then it could not only result in large-scale deaths but also affect the reproductive capabilities of those that survive. This could translate in to a sizeable impact on the world population of the affected species. Polar bears, for example, have, on an average two cubs every three years. This is a very low fertility rate – so, even if one polar bear is killed, the loss can be significant for the total population. Fish on the other hand are very efficient and lay eggs year round. Even if all their eggs at a particular time were destroyed, it would most likely not affect their overall population. However, if their breeding ground is destroyed then it can have a major impact on the total population depending on their ability and willingness to relocate to a new area to lay eggs, explains Nevalainen.
Due to lack of sufficient data on the number of species in the region as well as that on migratory population, it is difficult to predict future scenarios in case of an accident, she adds. “Depending on the extent of the spill and the ecosystem in the nearing areas, a spill can lead to anything from an unfortunate incident to a terrible disaster,” says Nevalainen.
©katiekk I Shutterstock
It might even affect the food chain, at a local or global level. “If oil sinks to the seafloor, some species run the risk of dying or migrating due to destroyed habitat – an example being walruses as they merely dive to get food from the sea floor,” adds Nevalainen. As the walrus is a key species in the food web, this has a high probability of upsetting the food chain.
When the final results of her study come through, Nevalainen aims to compare different regions of the Arctic and the probability of damage in these areas, as well as potential solutions to protect the ecosystem. This would include several factors. One of them could be breeding patterns – spring, for instance, is when certain areas need to be cordoned off for shipping activities, as most animals breed during this time.
“At the moment there are no mechanisms to deal with an oil spill in the Arctics. I hope that it never happens. The Arctic ecosystem is very delicate and it won’t take too much to disturb it, and the consequences can be huge, globally,” warns Nevalainen.
About the Researcher
Maisa Nevalainen is a third- year PhD student at the University of Helsinki, Finland. Her main focus is on environmental impacts caused by Arctic oil spills, while her main research interests include marine environment, and environmental impacts of oil spills among others. Nevalainen is working with the Arctic Futures Initiative at IIASA over the summer, with Professor Brian Fath as her supervisor and Mia Landauer and Wei Liu as her co-supervisors.
This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Jul 12, 2017 | Air Pollution, Demography
By Caroline Njoki, IIASA Science Communication Fellow 2017
Child mortality is high in Nigeria. For every 1000 children born, 128 deaths occur, according to the 2013 Nigeria Demographic and Health Survey report. This is one of the highest rates in Sub-Saharan Africa.
Although the Nigerian government is working hard to change the story and ensure more children live to celebrate their fifth birthday, through schemes such as free maternal and child healthcare, indoor air pollution may hinder those efforts if not addressed, research has shown.
Solid fuels and the health of children and women
“Indoor air pollution can have a severe effect on children’s health. For example, pneumonia, a major contributor of under-five mortality, will be exacerbated,’’ says Olugbemisola Samuel, a participant in the Young Scientist Summer Program who is currently working on a project to determine just how many lives could be saved by replacing solid fuels with clean ones in Nigeria.
Indoor air pollution poses a serious health risk to children and women in developing countries © Svetlana Eremina | Shutterstock.com
It is a common practice, not only in Nigeria but in many African and Asian societies, to find mothers carrying young children on their backs as they go about domestic tasks in the home. Women are likely to spend most of their time in the kitchen cooking, washing dishes, and heating water for drinking or bathing.
Cooking in rural households is done on traditional stoves where cow dung, crop straw, charcoal, and firewood are used. The smoke contains many harmful tiny particles and substances. If taken in small quantities over a long duration, this interferes with the respiratory system and can cause other health problems. In Nigeria, 80% of children under five years live in homes where wood is the main fuel used.
A 2016 report from UN Children’s Fund links the use of these solid fuels to respiratory diseases such pneumonia, asthma, bronchitis, impaired cognitive development, and cataracts among children under five years, especially in developing countries. For children and women with already weak immune systems from malnutrition, HIV/AIDS, tuberculosis or other chronic diseases, long-term exposure from indoor air pollutants can worsen the conditions.
Exposure to indoor air pollution during pregnancy and delivery can mean miscarriage, low birth weight, or children with stunted growth. A study carried out in India also associated the likelihood of developing preeclampsia (elevated blood pressure) while pregnant with long-term exposure indoor air pollutants.
Olugbemisola, in her current IIASA study, is using the Greenhouse Gas-Air Pollution Interactions and Synergies model to estimate the number of children under five years that may be prevented from dying if cleaner fuels (such as electricity and gas) are adopted. She hopes to share her findings with policymakers in energy and health sectors, especially in the areas severely affected by indoor air pollution and under-five mortality.
Tracing and addressing the problem
Income and wealth dictate the choice of fuel used in a household. Most rural households use solid fuel for cooking owing to their low income. In urban areas, where most people do have access to electricity, they may still rely on cheaper sources of energy such as charcoal and kerosene for cooking.
Making other cleaner forms of energy available and affordable is one way of reducing indoor air pollution (CC) Harsha K R
“Making electricity and gas available and affordable to households should be seriously prioritized by the government as a critical intervention to improve the situation. Currently, only 56% of households in Nigeria have access to electricity yet the country exports to neighboring countries such as Ghana and Benin,” says Olugbemisola.
Use of solid fuels is highest (at 98%) in the northeast region of the country, a survey by Nigeria’s National Bureau of Statistics revealed. This region also has high illiteracy, poverty, and rates of early child marriage. “Women with low or basic education lack adequate knowledge and information to enable them make informed choices as regards to maternal health, family planning, design or location of the kitchen including choice of cooking fuel”, says Olugbemisola.
She proposes innovative communication strategies to reach out to women, particularly in rural and remote areas with little or no education to raise awareness on the topic. The methods could include the use of performing arts, television and radio, and pamphlets prepared in vernacular languages to be made available at health facilities or distributed by community health workers.
Another area for improvement is the location and design of the kitchen. In most rural settings, the kitchen is either part of the main house or built separately but urban populations living in informal settlements usually occupy one room that doubles up as the sleeping and kitchen area. Poor ventilation traps the smoke and increases the concentration of tiny particles. Pollution could be reduced by installing chimneys, switching to improved cooking stoves and better ventilation to allow clear air to circulate in the kitchen.
Successful development and implementation of these interventions will help to see more children living to celebrate their fifth birthday.
References
Agrawal S & Yamamoto S. (2015). Effect of indoor air pollution from biomass and solid fuel combustion on symptoms of preeclampsia/eclampsia in Indian women. Indoor Air 25: 341-352
Gbemisola W. Samuel (2016). Underlying and Proximate Determinants of Under-five Mortality in Nigeria: Understanding the Pathways of Influence. Covenant University, Nigeria. PhD Thesis.
Gbemisola W. Samuel, Ajayi Mofoluwake P, Odowu E & Ogundipe Oluwatomisin M (2016). Levels and Trends in Household Source of Cooking Fuel in Nigeria: Implications on Under-five Mortality. Health Science Journal 10:4
This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Jul 3, 2017 | Data and Methods, Food
By Victor Maus, IIASA Ecosystems Services and Management Program
Nowadays, satellite images are an abundant supply of data which we can use to get information about our planet and its changes. Satellite images can, for example, help us detect an approaching storm, measure the expansion of a city, identify deforested areas, or estimate how crop areas change over time. Usually, we are interested in extracting information from large areas, for example, deforestation in the Amazon Rainforest (5.5 million km², around 15 times the area of Germany). It would be challenging for us to monitor and map such vast areas without combining satellite images with automated and semi-automated computer programs.
Aerial view of the Amazon Rainforest, near Manaus, Brazil. Monitoring deforestation in the Amazon is difficult because the area is massive and remote. ©Neil Palmer | CIAT
To address this problem, I developed — along with my colleagues Gilberto Camara from the Brazilian National Institute for Space Research and Marius Appel and Edzer Pebesma from the University of Münster, Germany — a new open source software to extract information about land-cover changes from satellite images. The tool maps different crop types (e.g., soybean, maize, and wheat), forests, and grassland, and can be used to support land-use monitoring and planning.
Our software, called dtwSat, is open-source and can be freely installed and used for academic and commercial purposes. It builds upon on other graphical and statistical open-source extensions of the statistical program R. Adding to that, our article in press in Journal of Statistical Software is completely reproducible and provides a step-by-step example of how to use the tool to produce land-cover maps. Given that we have public access to an extensive amount satellite images, we also get much benefit from tools that are openly available, reproducible, and comparable. These, in particular, can contribute to rapid scientific development.
The software dtwSat is based on a method widely used for speech recognition called Dynamic Time Warping (DTW). Instead of spoken words, we adapted DTW to identify ‘phenological cycles’ of the vegetation. These encompass the plants’ life cycle events, such as how deciduous trees lose their leaves in the fall. The software compares a set of phenological cycles of the vegetation measured from satellite images (just like a dictionary of spoken words) with all pixels in successive satellite images, taken at different times. After comparing the satellite time series with all phenological cycles in the dictionary, dtwSat builds a sequence of the land-cover maps according to similarity to the phenological cycles.
The series of maps produced by dtwSat allows for land-cover change monitoring and can help answer questions such as how much of the Amazon rainforest has been replaced with soy or grass for cattle grazing during the last decade? It could also help study the effects of policies and international agreements, such Brazil’s Soy Moratorium, where soybean traders agreed not to buy soy from areas deforested after 2006 in the Brazilian Amazon. If soy farming cannot expand over areas deforested after 2006, it might expand to areas formerly used for cattle grazing deforested before 2006, and force the cattle grazing farmers to open new areas that have been cleared more recently. Therefore, besides monitoring changes, the land-cover information can help better understand direct and indirect drivers of deforestation and support new land-use policy.
Further info: dtwSat is distributed under the GPL (≥2) license. The software is available from the IIASA repository PURE pure.iiasa.ac.at/14514/. Precompiled binary available from CRAN at cran.r-project.org/web/packages/dtwSat/index.html
dtwSat development version available from GitHub at github.com/vwmaus/dtwSat
Reference:
Maus V, Camara G, Appel M, & Pebesma E (2017). dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R. Journal of Statistical Software (In Press).
Maus, V, Camara, G, Cartaxo, R, Sanchez, A, Ramos, FM, & de Queiroz, GR (2016). A Time-Weighted Dynamic Time Warping Method for Land-Use and Land-Cover Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9 (8): 3729–39.
This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
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