understanding the economic challenges and impact of
TRANSCRIPT
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Understanding the economic challenges and impact of digital
exclusion on female migrant workers during COVID-19 pandemic:
Kuanwala Case Study
Minor Project Report
Submitted by
Saloni Rawat
For the partial fulfilment of the
Degree of Master of Arts in
SUSTAINABLE DEVELOPMENT PRACTICE
Department of Policy Studies
TERI School of Advanced
Studies
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About the Organization and the Internship
Social and Development Research & Action Group (SADRAG)
SADRAG is a not-for-profit organization having been in existence since 2004. It is currently
working in the geographical areas of North: Delhi, Noida, Greater Noida, Dadri and rural
communities of Western U.P. and in the South: Bangalore. With a firm belief in equality of
life for all, SADRAG envisions a world of dignity and self-respect especially for women
and children.
Observing the subservient social roles that bind women and hamper their growth, SADRAG
envisages a world that has no scope for gender discrimination, where men and women have
equal access to opportunities and availability of resources for growth and can participate
equally in social and community life. The children should have a free and healthy life that
goes with the community and family for mutual growth and development.
My internship entailed research-based work in a marginalized community in Dehradun.
During the internship with Social and Development Research & Action Group (SADRAG),
under the guidance of Dr. Mala Bhandari, I had the opportunity to explore and understand
the issues related to digital and economic inclusion of women through a review of literature as
well as witness the challenges and experiences of women in Kuanwala, Dehradun through
field investigation.
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Acknowledgement
I am extremely grateful for interning with the Social and Development Research & Action Group
(SADRAG) that provided me with a great opportunity to learn and sharpen my research skills.
I would like to present my sincere gratitude to Dr. Mala Bhandari for guiding me through the
Internship, sharing her valuable insights, and encouraging me to pursue research on a topic of my
interest. I also thank my supervisor, Dr. Chandan Kumar, for supporting us during the internship.
Finally, I am extremely thankful to the women of Kuanwala who hosted and helped me with the
interviews, and trusted me with their experiences and stories.
Thank you,
Saloni Rawat
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1. Introduction
Digital transformation – the consequences of digitization on economy and society – is opening up
new opportunities around the world, promising increased productivity development and higher
well-being for all populations (Pollitzer, 2018). Mobile phones, digital platforms, the internet, and
fintech solutions offer “leapfrog” opportunities that can help in reducing the gender digital divide
by providing women enhanced economic opportunities, more possibilities to earn, and access to
information, knowledge, and skills (OECD, 2018). However, there is still a large gender disparity
in digital technology access, usage, and ownership, which limits the equitable realization of the
advantages of digital transformation (GSMA, 2020; OECD, 2018). Digital technology is critical
for democratic participation, access to job prospects, health, economic security, government
benefits/schemes, and public services, social capital, and connections, and even preventing gender-
based violence, hence, bridging the gender digital divide also allows women to better cope with a
crisis (UNDP, IMF, and UN Women, 2021). ICTs like the Internet and broadband hold the
potential to better contribute to protection of women’s rights as well as their upliftment through
social, political and economic dimensions, that benefits not only women but also their communities
and the society (The UN Broadband Commission for Sustainable Development, 2017).
Unfortunately, the COVID-19 pandemic has exposed the vulnerabilities of the informal service
sector and sectors dominated by women (UN Women, 2020) that already faced the overlapping
issues of “capital, care, caste, gender, and climate” (ActionAid Association, 2020). ILO (2020)
report estimates that women in low-income and low- and middle-income countries are more
exposed to economic shocks as they work in informal sectors with no social security, no contracts,
poor wages leading to almost no savings and investments (Unni, 2020). This primarily includes
migrant workers who predominantly work informally in construction activities, small industries,
domestic work, and the hotel-restaurant industry (Aajeevika Bureau, 2020). Hence, the research
aims to understand the scope and challenges of utilizing digital technology as a means to improving
women’s workforce participation rate as well as their upward mobility in the society.
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2. Literature Review
The expansion of the service sector as a result of digitization gives opportunities for women in the
informal sector to earn a living through digital technology (UN Women et al., 2020). However,
technology alone cannot help with socio-economic development unless it takes into account the
realities of the people who will be using it (Pollitzer, 2018).
2.1 Low women’s workforce participation rate: What is the reason?
Prior to the COVID-19 pandemic, India had one of the lowest and continuously falling women's
Workforce Participation Rate (WPR), as well as a high rate of precarious informal work for which
women's inadequate skills have been highlighted as a barrier to their potential to obtain more and
better work (Mehrotra and Sinha 2019). Besides, cultural impediments on women working outside
the home, safe access to the workplace, and decreasing labor supply due to upward mobility of
poor households are also significant factors (Dewan 2019; Mehrotra and Parida 2017; Rukmini
2019). A common explanation that has also emerged in this regard is that young women and girls
with greater educational performance look for equivalent jobs, and the lack of which discourages
them from engaging in low-paying and low-value-added jobs (Desai, 2019; Mitra and Sinha,
2021).
However, an important factor that is often overlooked is that of the cost of unpaid care work for
women. This is evident in the fact that labor participation rates among newly married women,
particularly those with small children, are lower. While women have accepted their position as
primary caregivers at home, evidence from various reports suggests that if suitable opportunities
exist, more women desire to work outside their homes. According to an ILO and Gallup report
(2017), about 30% of women in India, that are engaged in household responsibilities for most of
their time, would prefer to work outside. NSSO 2014 survey data further reveals that around 60%
women above 15 years of age are engaged in domestic duties because “no other member will”.
The findings from the National Sample Survey data clearly reveal that the majority of women who
are not in the labor market are occupied with domestic responsibilities (Chandrasekhar and Ghosh
2020). In rural and urban areas, respectively, the share of women involved in care work and
domestic and allied activity was 57.4 percent and 60 percent, respectively, compared to just 0.5
percent and 0.6 percent for men in 2018–19 (Chakraborty, 2020). OECD (2021) data also shows
that around the world women spend considerably more time on unpaid care labor than males.
According to the time use survey conducted in India by NSSO, MoSPI and GOI (2019), men spend
222 minutes more on “paid and productive work” than women, but women spend 300 minutes
more on unpaid labor (household chores and caregiving) than men. It is therefore clear that while
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fulfilling family's unpaid and care demands, women face enormous opportunity costs. This task
and the time spent on it is often not recognized, leading to undervaluing and "invisibilisation" of
women's work (Mitra and Sinha, 2021).
Even after removing the care burden and household work, women were 7 times more likely to lose
their jobs during the pandemic and 11 times less likely to recover from job loss, which could be
likened to inequitable "employment arrangements" and "gender-based occupational segregation"
(Abraham et al 2020). A survey conducted by APU (2020) reveals that during the lockdown in
India, a greater number of women reported employment losses than men. It is anticipated that by
August 2020, 55 percent of temporary salaried female workers and 46 percent of self-employed
female workers had left the workforce (Abraham et al 2020).
Another challenge is the rise in informalization- the increasingly lacking implementation of labor
regulations, the rise in temporary jobs, the lack of contracts, the large-scale transition towards self-
employment, and the ambiguous definition of “work” and “worker”- they are all impeding the
realization of labor rights (Dewan, 2019). PLFS 2018-19 and NSSO 2020 data show that more
than 70% of urban female workers and over 60% of rural female workers in regular employment
had no formal job contracts (Mitra and Sinha, 2021).
2.2 Sector-wise challenges and relief measures
The central government announced an increase in daily wage rates for MGNREGA workers from
Rs. 182 to Rs. 202 during the pandemic, however, work was suspended in most places during the
lockdown, leaving only a few people to benefit from the wage increase (Naidu, 2020). This scheme
has the potential to have a big impact on the economy. However, even before the pandemic,
corruption, inadequate implementation, and underfunding limited its ability to generate jobs. In
2020–21, the annual budget allocated for MGNREGA fell by another 9,500 crores, a 13 percent
decrease, compared to 2019–20 (Shroff, 2020).
Cash transfers under the COVID-19 stimulus packages amount to around 9% of total of monthly
GDP per capita, which is significantly less than the average allocation of 26% by 115 countries,
according to a World Bank Report (Gentilini et al 2020). These cash transfers reached just about
15% of the population (Gentilini et al 2020), indicating that they do not reach a large number of
working individuals who face precarious livelihoods and lives.
Furthermore, for three months, the public distribution system (PDS) allotment for all households
under Antyodaya Anna Yojana was boosted by 1 kg pulses along with 5 kg wheat or rice per
individual, which is barely enough to compensate the losses family's incurred due to pandemic
(Naidu, 2020). For the migrants who were left out from the National Food Security Act or did not
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have a ration card, two months of free food grains were also announced, however the
implementation was not carried out appropriately (Naidu, 2020).
Construction Workers: Some relief measures were announced by the Centre according to which
18 states transferred Rs 1,000–5,000 from specified cess money under the BoCW Act to bank
accounts of registered construction workers affected by the COVID-19 outbreak. States paid a total
of Rs 2,250 crore in the form of one-time cash benefits to nearly 18 million construction employees
who were in financial hardship. In Uttarakhand, around Rs. 2000 were transferred per worker.
However, Unni (2020) notes that based on the PLFS (2017-18) estimates, there are over 26 million
construction workers that are not registered in the BoCW Act and hence will be left out from the
Direct Bank Transfer Scheme.
Street Vendors: Around 20 crore Jan Dhan women account holders would be compensated with
Rs 500 per month for three months (Unni, 2020). The benefits of loans, according to Arbind Singh,
national coordinator of the National Alliance of Street Vendors of India (NASVI), are unlikely to
bring help and solutions like direct cash transfer are urgently needed. The National Hawker
Federation's Ghosh suggested looking for interest-free loans and MUDRA loans with subsidies
(Sen 2020).
Domestic Workers: Domestic workers were more susceptible since they depended on their
employers due to a lack of social security coverage and access to credit. Other issues experienced
by domestic workers and other informal employees were a lack of rations, with only a few workers
receiving free rations and direct government benefit transfers.
Manufacturing Sector: In 2018–19, about 14% of women worked in the manufacturing industry,
and the pandemic has hit the industry hard. The industry is labor-intensive, and it frequently
employs low-paid and low-skilled women. Since there has been a reduction in effective demand,
especially for non-essential commodities, workers employed in the sector are at risk of being laid
off.
Self-employed: The majority of women in self-employment operate as unpaid helpers in family
businesses or run their own businesses without external help, and only a few have managerial roles.
Self-employment largely falls into the category of unpaid labor on family farms and businesses,
exposing its gendered nature (Mitra and Sinha, 2021).
2.3 What can digital technology do?
New industries such as overseas production as well as traditional sectors like agriculture,
manufacturing, and health, are all being transformed by digital technology. ICT is also critical for
economic and productivity growth. In LMICs, while social media and messaging remain popular,
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more people have been realizing and accessing the benefits of services like educational and health-
related information, and employment opportunities. Thus, consumption is becoming more diverse
and productive (GSMA, 2020).
Several studies suggest that the digital transformation can also solve the inadequacies in the
unorganized sector, formalize labor relations, and expand job and income-generation prospects for
women (Global Compact Network India & Deloitte, 2019). The development of the service
industry as a result of digitization gives opportunities for women in the informal sector to earn a
living by making use of digital assets. Various women's issues have also been addressed via digital
platforms since they give them more time and mobility, make it easier for them to access open
marketplaces, provide information symmetry, and connect them to specialty markets (UN Women
et al., 2020).
Mobile Banking or “shadow banking” is also a great tool to enhance financial inclusion of women.
It is a form of banking service that is convenient, cost-effective, and occurs through digital
channels outside of the formal banking system and hence offers financial services to the
“unbanked” population as well (OECD, 2018). As a result, it is crucial to utilize efficient,
sustainable, and high-quality digital financial services to improve the financial inclusion of women
while making sure that consumers are protected from false or malicious practices, and the financial
sector remains stable (OECD, 2018). Mobile money has proven to alleviate long-run poverty and
alter women's financial behavior. Women have also discovered that mobile money is a component
that makes it easier for them to establish a business. It has the potential to further impact migration
and economic prospects, as well as diminish women's reliance on several part-time jobs (Suri and
Jack, 2016).
Agriculture, healthcare, education, financial services, energy, logistics, and retail, along with
public services and labor markets, are among the newly digitalizing sectors that could generate
$10 billion to $150 billion in new economic value by 2025, as digital tools in these sectors help
improve output, save time and costs, reduce fraud, and improve demand-supply linking (McKinsey
Global Institute, 2019). Hence, by 2025, McKinsey Global Institute (2019) estimates that the
digital economy's productivity might release 60- 65 million jobs, many of which will require
relevant digital skills.
2.4 Challenges in accessing digital technology
While satellite technology, among other things, has eased the widespread use of mobile phones
and (nearly) global coverage, women continue to be disproportionately disadvantaged due to their
lower ownership and the use of mobile phones and smartphones (GSMA, 2018). According to data
from NSS-MoSPI (2017-18), only 38% of women own mobile phones, and 12.8% use computers,
while usage for men stands at 71% and 20% respectively. Furthermore, only 8.5% of the female
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population in rural India can use the internet as compared to 17.1% of the male population.
Interestingly, even when they have access, the digital gender disparity persists in usage as women
are 18% less likely than males to utilize mobile Internet. In India, there is a 10% gender disparity
in the use of mobile internet (GSMA, 2018).
Affordability is a major problem for everyone, but it impacts women and girls more
disproportionately, and it is still one of the most significant barriers to ICT (Information
Communication Technologies) adoption. Furthermore, when technology sophistication and cost
of ownership increase, the digital gender disparity is seen to widen (OECD, 2018). According to
Intel and Dalberg (2012), 25% of women that don't use the Internet are typically uninterested in
doing so, and most of them feel that internet usage is of no advantage to them (OECD, 2018).
While women largely cited disinterest and low expectations about its usefulness as reasons, lack
of faith in digital technology or the Internet might also play a significant role.
The most significant barrier to smartphone ownership and usage in India is a lack of reading and
writing skills, according to the Mobile Gender Gap Report Survey in 2019. The survey also
reported that India has the largest gender gap among all the Asian nations surveyed under the
report. Reading and literacy skills are a precondition while accessing digital tools. Web search
skills include not only reading and typing skills but also the ability to search, comprehend,
interpret, organize, and filter the content. Greater cognitive strategies, visual-spatial abilities,
problem-solving skills, self-organization, or interpersonal skills are required to keep up with the
changing requirements of the digital world that might lead to gender gaps in schools and the labor
market (Lee, 2007; Spiro et al., 2015; OECD, 2018). Thus, illiteracy makes it even more difficult
for women and girls to use online services (Social and Political Research Foundation, 2020).
Illiterate women appear to exclusively use digital services that are more known to them or are
easier to use, such as Skype and YouTube. Search engines like Google have added voice
navigation systems in local languages to improve inclusivity and accessibility in Web search
queries, in an attempt to overcome this barrier (OECD, 2018).
Other factors such as education, employment situation, and economic level simultaneously
contribute to such "technophobia." Even after receiving formal education, girls appear to lack
confidence in ICTs, which is often caused or exacerbated by societal and parental biases, as well
as parent's expectations. This results in self-censorship by young girls and lower participation in
ICTs (Global Compact Network India & Deloitte, 2019).
Female Internet users are currently using fewer services than male users and are less confident in
their use of the Internet. Although mobile money accounts are an efficient tool to increase financial
inclusion, women are less likely to own and utilize them. Especially women may receive help from
online or video-based upskilling and courses that help them make effective use of digital
technologies and obtain more benefits from them (OECD, 2018).
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Given the inequitable access to and use of skills, skill development efforts that are more gender-
responsive can potentially be agents of change for boosting societal mobility from education to the
labor market, unpaid to paid work, and lower-end jobs to higher-end jobs. However, training
programs alone are not enough. There must be a linkage between training programs and industry
requirements, especially as a greater number of girls are completing secondary level of education,
particularly in rural areas. These girls need to have access to skills training closer to their homes
(Sinha, 2019).
In developing and emerging economies, safety concerns are frequently recognized as a key factor
for families' objection to women and girls using the Internet or owning a mobile phone. Women
and girls who use the Internet face more hazards such as cyberstalking, online harassment, etc.
thus developing methods to safeguard and prevent online gender-based violence is critical (UN
Broadband Commission for Sustainable Development, 2017).
2.5 Current Initiatives and Gaps
Digital technologies are being used by India's current social policies to separate social and
economic rights from their deeply gendered roots. There are gendered implications of privatization
of social security. In 2020, the state provided a Rs 5,000 crore stimulus package for roughly 50
lakh vendors, recognizing the devastating impact of livelihood loss during the first wave of
COVID-19 (Majithia 2020). However, due to a male prejudice at the operational level, the Rs
10000 offer for all vendors as an initial working capital has not helped women vendors (Unni
2020). The Pradhan Mantri Jan Dhan Yojana program is also aimed at increasing women's
financial inclusion at a national level, including promotion of digital wallets or online banking
based on mobile transactions with the help of telecom operators and the establishment of Cash Out
Point facilities (PMJDY, 2018). However, literature suggests that assuming monetary transfers
and women's empowerment are inextricably linked can be deceptive. Cash transfers, in many
cases, may perpetuate traditional gender norms while ignoring gender inequalities within the
household (Gurumurthy, Chami and Thomas, 2016). Dewan (2019) argues that there is a need to
integrate gender in the framework of government policies at the inception stage itself as
government programs often retrogress due to a gender-neutral outlook.
Gender resource centers are being integrated through the National Rural Livelihood Mission
(NRLM) in order to empower women and promote women leaders and entrepreneurs. Some of the
main interventions have been as follows; designing skill development programs (DDU-GKY
PMKY), which seeks to improve women's ability to use technology, improving accessibility to
digital platforms and encouraging partnerships with start-ups dedicated to helping women with
financial technology solutions, and facilitating credit facilities through low-value MUDRA loans
(OECD,2018; UN Women et al., 2020; Patel, 2021).
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All of these programs are largely aimed at turning women into entrepreneurs in order to increase
women's engagement in the workforce. While these policies have been extensively promoted, the
government's official data shows that they have had little impact on the country's Female Labour
Force Participation Rate (Mitra and Sinha, 2021). The designs are highly gender-neutral and do
not have strategic initiatives that focus on providing women with the skills essential for actively
participating in the digital economy (Gurumurthy, Chami and Thomas, 2016). The National Digital
Literacy Mission (NDLM) scheme, aimed at making one individual digitally literate in eligible
households, also pays insufficient attention to the issue of skill development of women and other
underrepresented groups.
3. Research Question
Women in low-skilled jobs may face more alterations in their work than males as the digital
transformation continues to expand and penetrate all industries. This could be due to the possibility
of machines replacing (parts of) human jobs, resulting in the necessity to perform diverse duties
on the job, as women undertake more routine chores than males (OECD, 2018). Especially due to
COVID-19, women’s WPR has declined further, causing severe socio-economic impacts on
women. In such a scenario, where utilizing digital technology becomes inevitable not only while
working but also to overcome the crisis caused due to pandemic, what are the challenges that
women are facing while accessing digital technology and benefitting from it, and what can be done
to improve their digital skills?
4. Research Objectives
1) To determine whether women have the skills necessary to navigate the workplace in a
digital economy or not
2) To understand impact of digital intervention on improved economic opportunities and
social empowerment of female migrant workers
3) To discuss the scope and challenges of utilizing digital platforms to increase women's labor
force participation
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5. Methodology
The study aims to understand the livid experiences for which the most appropriate design is
qualitative research. It is empirical and thus, helps to make sense of the gathered data by testing it
against ideas, theories and hypotheses by explaining it either through the participant’s point of
view, the etic approach, or through the researcher’s perspective, the emic approach. This helps to
produce research that is guided by theory while expressing the subject’s perspectives to best
understand the social realities and problems. (Smith, 1987)
Further, the research method used is descriptive and aims to elucidate and interpret the findings of
the current state. It helps to best describe the accounts, phenomenon, conditions, practices, and
challenges to communicate the participants’ experiences (Creswell, 2007).
The sample population will consist of female migrant workers from Kuanwala, Dehradun. Within
Kuanwala, the localities of Kuanwala I (IMCL Factory area), Kuanwala II (Choona-Bhatta Factory
area) and Nirmal Basti have been chosen. A sample size of 50 individuals will be selected for this
purpose. The population will be selected through purposeful sampling based on the researcher’s
judgment to get in-depth and unique experiences (Taherdoost, 2016).
Rationale: Kuanwala is an industrial area located in the outskirts of Dehradun city, that formally
came under Nagar Nigam in 2019. It has a total population of 1,779 with 15.85% population of
Scheduled Castes (SC). Most of the families have migrated here from villages in Uttar Pradesh
and Bihar; and predominantly work in factories like IMCL (Indian Made Commercial Liquor)
Factory, Choona-Bhatta Factory, Textile Industry, Industry showrooms, or at brick kilns and
construction sites. Being an industrial area, the residents have been directly facing the adverse
effects of pollution in the form of contaminated air with a foul smell, a phenomenon that has
previously given rise to the ‘Environmental Justice’ movement that argues how minority
populations have had been suffering disproportionately due to pollution suggesting that social
inequities are linked to environmental issues (Banzhaf et al., 2019).
Additionally, some of the families live within the factory housing in a single room, often times
with no washroom facility, and share a community tap water. They also do not have a healthcare
facility in the vicinity. Such living conditions are especially difficult considering the COVID-19
pandemic situation wherein the residents cannot maintain appropriate physical distancing norms
since they are living in close proximity, and have to travel long distances for health-related
services. For women, these problems increase tenfold as they have to bear the burden of care work,
lack of privacy at home, unsafe work environment, and hygiene and health issues among other
things. Furthermore, Anand and Thampi (2020) estimate that Scheduled Castes (SCs) earn roughly
55% less than the other caste categories (excluding Scheduled Tribes (STs), and Other Backward
Classes (OBCs)), with the disparity being greater in urban areas than rural areas. According to
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Oxfam (2020) research, women workers in India are paid less regardless of their employment
status (casual vs. regular/salaried), sector (organized vs. unorganized), or location (urban vs. rural).
Occupational segregation, along with explicit and implicit biases, contributes to income disparities
across caste and gender boundaries (Kapil, 2019). These income disparities then force families to
marry their daughters at a younger age as they consider them a burden. Consequently, women get
stuck in a vicious cycle of illiteracy, low skills, low wages, and low employment rates.
To understand impact of digital interventions on improved economic opportunities and social
empowerment of female migrant workers, and to determine whether women have the skills
necessary to navigate the workplace in a digital economy or not, focus was put on secondary
sources in the form of research papers, journals, articles, and news reports along with insights from
the primary data collection through interviews of the sample population. For the last objective, to
discuss the scope and challenges of utilizing digital platforms to increase women's labor force
participation in Kuanwala, primary data collection through structured interviews of the proposed
population was referred.
6. Primary Research
6.1 Demographic Details
Age:
Figure 1: Age
Around 48% women of the respondents belong
to the 30-35 years age group, while 18% belong
to 25-30 years, 16% to 20-25 years and 14% to
35-40 years age brackets.
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Literacy Level:
Literacy and education levels are basic indices
of development. Literacy is a crucial component of an
individual's development since it allows them to better
understand their social, economic, political and
cultural surroundings. The literacy levels adapted
from Census data for the purposes of this research
study are as follows: Illiterate, Below Primary,
Primary, Middle, Secondary, High Secondary,
Graduate and above.
40% of the respondents are ‘Illiterate’, while 10% have ‘Below Primary’, 14% have ‘Primary’,
12% have ‘Middle’, 14% have ‘Secondary’, 6% have ‘High Secondary’, and 4% have ‘Graduate
and above’ levels of education.
Caste:
76% of the respondents belong to Scheduled Castes
and 10% to Other Backward Castes category.
Migrant:
The migrant population has been chosen on the
basis of “last place of residence”. 42% of the
respondents have been living in Kuanwala for
“more than 15 years”, 30% have been living for
“10-15 years”, 22% have been living for “5-10
years” and 6% have been living for “less than 5
years”
Figure 2: Literacy level
Figure 3: Caste
Figure 4: Migrant Status
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Housing:
Figure 5: Housing
The housing situation and assets available in
the household reflect the people's living
conditions. Depending on the nature of the
material used in walls and roof, ownership
status houses have been classified as: Kuccha,
Semi-pukka, Rented Room/house, Community
housing, Own house.
38% of the respondents lives in ‘Rented room/house’, while 26% live in their ‘own house’, 22%
live in ‘semi-pakka house’, 12% live in ‘Community housing’, and the remaining 2% live in
‘Kuccha house’.
Amenities and assets:
Figure 6: No. of Bathrooms Figure 7: Private Access to water
The quality of life of people also depends on the amenities and assets available to them. For this
purpose, questions related to number of rooms, bathroom and latrine facility, electricity, private
water connection, assets like refrigerator, TV, mobile, bicycle, motorbike etc. have been asked.
10% of the respondents have ‘No bathroom’ while 4% of them have ‘2 bathrooms’, 2% have access
to ‘Community bathroom’ and other 2% have more than ‘3 bathrooms’. Around 72% have a private
access to water connection while the remaining 28% use community tap.
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Social Security:
Figure 8: Social Security
All the respondents responded “none” when asked about social security in the form of PF, Health,
Maternity Benefits, Pension etc. None of the respondents had a Jan Dhan Account which means
that they lost out on Direct Benefit Transfer relief schemes. 22% respondents also did not have a
ration card and hence did not receive PDS benefits.
Time Use:
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Time Use data expresses how people utilize their time on different activities throughout the day.
It is divided into paid work, unpaid work, care work, personal care, leisure, and unspecified time
(OECD, 2021). For this research study, unpaid work and care work have been put in the same
category- “unpaid work”; and personal care and leisure have also been added in the same category-
“personal care”. Unpaid Work includes taking care of domestic animals, looking after the family,
cooking food, cleaning, collecting water. The time-use data presented is the best approximate data
based on the interviewee’s responses.
Evidently, women are spending more no. of hours on paid work and unpaid work than skill
enhancement or learning and personal care.
Of those involved in paid work, around 38% are working for “8-12 hours” and 8% are even
working for “more than 12 hours”. This is one of the drawbacks of informal or unorganized sector.
In case of unpaid work, that also includes care work, 28% spend “4-8 hours”, 52% spend “8-12
hours”, and 6% spend “more than 12 hours”.
98% respondents spend around “1-4 hours” on personal care and leisure.
Consequently, 76% women do not spend any time on skill enhancement or learning, with only
14% spending “0-1 hours”, 6% spending “1-2 hours”, and 2% spending “2-4 hours” and “more
than 4 hours” each.
6.2 Employment Details
Economic Activity:
The economic activities have been divided under the following major sectors: “Agriculture”,
“Manufacturing and Allied Industries”, “Construction” and “Service”.
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36.1% of the respondents are involved in ‘Manufacturing and allied industries’ for their source of
employment while 27.8% of respondents are involved in ‘Construction’, 19.4% is involved are
‘Service’ and 16.7% are involved in ‘Agriculture’.
In case of their partners, around 58.7% are involved in ‘Construction’ while 26.1% in ‘Service’,
8.7% in ‘Agriculture’ and the remaining are involved in ‘Manufacturing and allied industries’.
Employment Status:
Regarding the employment status of the respondents’ and their partners’, more women have clearly
left the workforce. If we examine the situations of “pre-COVID-19 (January-March 2020)” and
“after COVID-19 first wave (September 2020- February 2021)”, number of women who were
unemployed and left the workforce increased 26% to 52%. As estimated by several reports, there
was a surge in unemployment rate “during COVID-19 first wave (April-May 2020)” and around
92% women left the workforce. There is no change between “after COVID-19 first wave
(September 2020- February 2021)” and “during COVID-19 second wave (April-June 2021)” for
women, indicating that number of women that had re-entered the workforce continued to work
even during COVID-19 second wave.
For the partners of the respondents, all of them were working “pre-COVID-19 (January-March
2020)”, and 91% of them lost their jobs “during COVID-19 first wave (April-May 2020)”. 87%
of them reentered the workforce “after COVID-19 first wave (September 2020- February 2021)”,
and 15% were still unemployed. Out of 87%, 61% continued to work even “during COVID-19
second wave (April-June 2021)”. The unemployment rate is evidently higher for women than men
throughout the pandemic.
19
Method of Salary Payment:
Figure 9
28% of the respondents receive ‘Regularly Monthly
Salary’, while 54% of them receive ‘Piece Rate
Payment’, 10% receive ‘Regular Weekly Payment’,
and the remaining 4% receive ‘Daily payment’.
Contract-Based Work:
51% of the respondents are employed through or work with a contactor while the remaining 49%
are not, and a 100% of the respondents do not have any written contract.
This informalization results in their labor right not being acknowledged. This further creates higher
chances of exploitation, poor workplace conditions and no fixed salary or wages.
Wages during and before the lockdown:
20
Of the 22.2% respondents who did not receive their wages for the work they did before lockdown,
19.4% were “unsure of receiving it” while 2.8% were “sure of receiving it”. Remaining 77.8%
received the wages for the work they did before the lockdown.
Further, 82.9% of the respondents did not receive salary for the duration of the lockdown from
their employer, while 17.1% did. Those who did receive were either employed in public
institutions or as domestic helpers.
Skills:
The respondents have a variety of skills. Majority of them, around 35.4%, have ‘Stitching/
Tailoring’ skills, 16.7% have ‘Craft’ related skills, 11.5% are good in ‘Cooking’, 8.3% of the
respondents know ‘Achar Making’, 8.3% also know ‘Toy Making’. 5.2% of them have
‘Grooming’ skills, other 5.2 % have ‘Embroider/ Crochet’ skills, and 4.2% have ‘Knitting’ skills.
2.1% of them know ‘Candle Making’ while 1% of them is good in ‘Driving’, 1% has ‘Athletic’
skills, and another 1% has ‘Computer skills’. Such skillsets open up opportunities for
entrepreneurial ventures that can be utilized more efficiently with the help of digital tools.
21
6.3 Digital Literacy
Personal Phone:
34% of the respondents have their personal phone while 66% do not have their own phone. Out of
all the respondents who have their own phone, 81.6% has a smartphone while 18.4% did not.
Additionally, 84.8% of the respondents' partners have a personal phone while the remaining 15.2%
do not.
Shared Phone:
4% of the respondents share it with their husbands,
while 25% share it with both their children and husband,
and 46% of them share it with their children. Most of the
respondents who are sharing their phones, do not even
have joint ownership. In case of most of the respondents
who are sharing their mobile phone with their children,
the children claim ownership especially due to the shift
towards online education and them being more digitally
literate than their mothers.
Usage:
Figure 11
Figure 10
22
Respondents were asked to rank the following services from 1-5 in terms of how much they use
it: Entertainment, Communication, Learning, Financial Transaction, and Employment.
All the respondents use the communication service through phone calls the most, while 42%
women use entertainment services the most. Learning, Financial Transaction and Employment
were ranked low as most women did not use these features. Interestingly, women with low literacy
levels, still preferred to watch “skill-enhancement videos” that they can imitate and learn, over
“entertainment videos”.
Social Networking Platforms:
64% of the respondents use social networking apps
while 34% of them do not use social networking
apps and the remaining are not sure.
Respondents were asked about the following
platforms: Facebook, Instagram, YouTube,
WhatsApp, Telegram, Twitter, Email, Paytm/
Google Pay/ Phone Pay, Yes Madam, Uber/ Ola,
Google Maps, Just Dial, Mahila E-Haat and Swayam.
Most of them know about Facebook, YouTube, WhatsApp, Google and some of them even knew
about Paytm/ Google Pay/ PhonePay, Ola/Uber, Twitter and Google Maps. However, in terms of
usage, 48.7% used Facebook, 76.9% used YouTube, 74.4% used Google,12.8% used Paytm/
Google Pay/ PhonePay, and 2.6% used Google Maps.
None of the respondents knew about platforms like Just Dial, Yes Madam, Mahila E-Haat and
Swayam that provide income and skill-enhancement opportunities.
Abilities and Digital Skills:
Figure 13
Figure 12
23
Figure 14
Respondents were asked to rate their abilities to use smartphones, making and receive phone calls,
ability to use the Internet (Internet literacy), typing skills, web search skills, ability to use the
computer (computer literacy) from 1-5 (1=lowest, 5=highest).
Most of the respondents can make or receive calls successfully, but are not confident about or
equipped with the other skills. Only 28% of the respondents feel that they can successfully use a
smartphone. Around 40% do not have typing skills and 30% do not have web-search skills. Only
2% of respondents have computer skills. In terms of internet literacy, a mixed response was
received, as some respondents are able to surf the internet through voice features and reading skills,
while others are dependent on family members.
88% respondents can take digital photos, 62% can record digital videos, and 50% can record digital
sounds. In terms of higher digital skills of editing photos, videos and sounds, and downloading
applications, more than 70-78% of respondents were not confident.
Platforms for employment opportunities and skill-enhancement:
84% of the respondents do not know about the employment opportunities with the help of digital
tools while 12% of them are not completely sure and the remaining 4% know of some opportunities
under which they cited ‘YouTube’.
24
70% of the respondents do not know about the platforms that can help them in developing/
enhancing their skills while 30% of them who knew about such platforms cited ‘YouTube’ and
‘Google’ as learning platforms through which they search and are able to learn through Audio-
Visual content.
Support while accessing digital technology:
100% of the respondents were not aware about the Digital Saksharta Abhiyan (DISHA) or National
Digital Literacy Mission (NDLM) Scheme and 100% of the respondents do not receive support
from any organization while accessing digital technology while 92% of the respondents do not
receive support from any organization to enhance or learn new skills. The remaining 8% that have
received support have mentioned about a Self-Help Group or SHG that was formed a few years
back but got dissolved once the community came under Nagar Nigam and nobody took leadership.
“Do you want to improve your skills to use internet and smartphones efficiently?”
Figure 15
25
80% of the respondents want to improve their skills to use the internet and smartphones efficiently
while 12% do not want to improve their skills and the remaining 8% were not sure.
The 12% who stated that they “did not want to improve” did not feel that internet skills or using a
mobile phone can help them with economic opportunities. They also expressed some
disassociation with digital tools and were dismissive about accessing them. They felt that it is
something their children can better learn. Their words indicated that they were either
uncomfortable while using mobile phones, or associate ‘shame’ with spending their time while
watching videos. The 8% who were unsure felt that they can improve if it is required of them and
if they find an appropriate job opportunity for it.
Challenges in accessing Digital Technology
Figure 16
The respondents faced several challenges while accessing digital technology but the most common
challenge was of illiteracy or lack of skills. 16.2% lack appropriate skills, 14.5% have “difficulty
in typing” as they do not know how to write as well, while 12.8% face “difficulty in reading”.
14% share their phone with other members and hence are not able to access it, 8.4% do not have
time, while another 8.4% have “lack of information” around usefulness of digital tools.
6.7% have “nobody to teach or help”, 5% are not allowed to use the internet, 4.5% are not
interested in it, and 2.8% feel it is unsafe. They also felt that they will be bothering their family
members if they constantly ask for help.
3.9% respondents do not use mobile phones and internet as they are expensive, 2.2% lack internet
connection and 0.6% face a lack of network coverage.
26
As mentioned in the literature, to overcome these challenges, especially literacy-related, women
often use voice-typing or voice-search features to access the different digital platforms, and video
content is also popular among them. A generational gap is also evident in women’s perception of
the benefits of technology. The hesitancy in adopting digital tools, especially platforms related to
financial transactions, also stems from having low confidence in self and a fear of the consequences
of making a mistake. Additionally, early marriage or child marriage is a rising trend in the
community that is discouraging young girls from continuing their studies or pursuing their
interests. Ironically, there are also cases (around 6%) wherein the girls have been made to drop out
after middle school for being good in management and accountancy, and are now managing the
family store/ shop/ business.
“I am about to get married and I don't have a personal phone. No one allows me to use it.”-
Shabnam, 21 years old, 8th pass
“I fear that I might press the wrong buttons etc. I try to use the phone only when my daughters
are with me.”- Umravati, 38 years old, Illiterate
“I try to take out time after I come back home from work but my parents will marry me if I try
jobs that are uncertain.”- Kunti, 22 years old, 8th pass
“I want to learn more as I really feel helpless right now, if someone can teach me how to use
phone in a better manner, I really want to work. I can only ask for help from my children but
they are busy.”- Nirmala, 34 years old, 5th pass
However, there are also instances wherein women have been learning with the help of digital tools
and are also carrying out financial transactions through digital platforms.
“I helped my mother-in-law to expand her kitchen service. We recently started taking orders
through phone calls and WhatsApp, and have been carrying out financial transactions through
PhonePay”- Shivani Yadav, 25 years old, MA pass
“I have been carrying out transactions through Google Pay and Paytm in our store as it is more
convenient.”- Seema, 20 years old, 8th pass
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7. Way Forward
Kuanwala is a close-knit community with families that get influenced by each other. Community-
led programs, adult literacy programs, and skill development initiatives are the need of the hour.
Households do not recognize the potential their daughters, wives, and daughters-in-law have, and
thus they neither allow them to work or learn, nor do they want to spend any additional resources
on them. Many women are unemployed even when the family’s financial condition is not good
because over the years the community and the women themselves have internalized the belief that
they are not qualified to work anywhere. As a result, lack of skills and illiteracy end up being the
biggest challenge in improving digital inclusion.
Removing barriers to adult education is critical for all, especially for women. This necessitates
more flexible options for adults to improve their skills, as well as coordination across actors and
institutions, such as employers, CSOs, and training and educational institutes. In order for women,
and men, to profit from the job prospects provided by digital technologies, efforts must be made
to guarantee that job flexibility does not come at the expense of job quality (UN Broadband
Commission for Sustainable Development, 2017).
Furthermore, women's engagement in (digital) labor markets would be aided by a greater sharing
of unpaid housework and child care. Actions aiming at raising awareness, challenging gender
stereotypes and norms, as well as policies promoting gender-neutral parental leaves and child care
services provision, would help to alter internalized societal norms, attitudes, and behavior around
childcare and housework. Closing the gender gap, including the digital one, necessitates initiatives
that address the structural reasons for the divide. Increased numbers of girls and women studying
STEM will do little to close inequalities if these individuals face the same biases in the workplace
(GSMA, 2020; GPFI, 2020; UN Broadband Commission for Sustainable Development, 2017;
OECD, 2018).
To embolden the digital strategy for gender justice, alternate social, political, and economic
discourses must be created in the information society (Gurumurthy, Chami and Thomas, 2016).
The idea of enabling accessibility includes the material means, abilities, and attitudes needed to
engage in the information society's social paradigm (GSMA, 2020). Women's ownership and
control of local media processes must be encouraged through policies that provide gender-
responsive public access spaces at the community level and establishing digital literacy programs
with a citizenship focus. This entails a focus on the link between women's online inclusion and
their equal standing in economic and political roles in the society, as well as freedom from
surveillance and intrusions into their privacy (Gurumurthy, Chami and Thomas, 2016). In this
regard, digital initiatives in many parts of India can be referred, such as:
28
• The Khabar Lahariya initiative in Bundelkhand is a women led community news reporting
initiative that encourages women to become reporters who use different digital tools to
capture and write news reports, and highlight the concerns of marginalized women in rural
UP that are not covered by mainstream media.
• Through the Young Women's Leadership Program, Feminist Approach to Technology
focuses on equipping young women from marginalized communities with technical skills
as well as critical digital literacy.
• IT for Change has prioritized the creation of new knowledge, information and data cultures
via women-run open access points that emphasize marginalized women's citizenship.
• TARA AKSHAR program by Development Alternatives is a 56 days adult literacy
program that incorporates and utilizes ICT to provide women with basic literacy skills.
• Jubilant Bhartia Foundation along with iDream Social ed-tech Foundation provide e-
content in local languages under their digital literacy program. While it is currently aimed
at providing primary education to children, it has recognized the resources required to
target women from rural and marginalized communities.
• SADRAG (Social and Development Research & Action Group) have developed a Digital
Bank model through which they are linking potential digital tool donors with people from
the marginalized communities, to work on the challenge of affordability. This is followed
up by a basic training on using the tools and monitoring its condition for 2 months and
replacing it if required.
• Skill Sakhi initiative of Government of Maharashtra with UNDP provides young women
with access to digital technology, addressing the knowledge gap on skill development and
creating local changemakers.
These efforts highlight the necessity for a national digital policy framework that addresses
women's status through a citizenship approach by focusing on women's rights and the entitlements
that address their marginalization and distress in the context of a global information society
(Gurumurthy, Chami and Thomas, 2016).
Fortunately, Gender-Responsive Budgeting in the Union Budget 2021-2022 has allowed for
allocation of Rs 120 crore (almost 40%) of the allocations to Pradhan Mantri Gramin Digital
Saksharta Abhiyan/ NDLM, a digital literacy program for rural areas, in recognition of the need to
be digitally included. This is the first time that Gender Budget has included a portion of the
PMGDISHA in its statement due to which women's access to opportunities offered by digital
platforms may improve (Mitra and Chaudhry, 2021).
However, Gender-Responsive budgeting strategies should be applied to all disbursements in all
ministries and departments; subsidies for all public goods, including food, water, health, energy,
education, and transportation should be increased; gender-diverse monitoring and evaluation
techniques should be developed and applied; and public service distribution should be improved
(Desai, 2019; Mitra and Sinha, 2021). Government schemes and programs that cater to providing-
29
better household infrastructure like toilets, piped water supply, housing, electricity, LPG etc.;
childcare facilities like the National Crèche Scheme (NCS) and Integrated Child Development
Services (ICDS); provision of prevention and mitigation strategies for gender-based violence
through helplines and shelter homes; access to education and healthcare; investments in decent
work environment for women, re-integration of women in labor force through wage incentives,
training programs, skill development initiatives- are all crucial towards encouraging and
facilitating a good environment for women to learn, develop skills and participate in the workforce
(Dewan, 2019).
8. Conclusion Digital technology offers vast opportunities for women empowerment and for equitable female
participation in the labor market, financial market, and entrepreneurship. Existing government
schemes and programs, such as social security programs, can be revamped to promote women’s
economic and digital inclusion as well. By utilizing digital technology more widely for
management, payment, and monitoring, the initiatives may improve women's digital participation
while also lowering program costs. There is also scope for further research on replicating the
successful digital models like SADRAG and case studies like Khabar Laharia, at a larger scale.
Furthermore, additional research on the vulnerability of female labor force participation in
developing countries that rely on low-skilled labor is critically needed.
Enabling girls and women via targeted education and re-skilling programs, as well as reforming
normative constraints, can expedite their learning and improve their skill sets. Consequently,
women will be able to emerge as equal stakeholders in the workforce, households, and
communities.
30
9. Annexure
INTERVIEW SCHEDULE
I) DEMOGRAPHIC DETAILS:
1. Name
2. Age
3. Sex
4. Address
5. Occupation
6. Education:
• Illiterate
• Primary
• High School
• Matriculation and above
7. How long have you been working?
8. Distance to work location:
9. Family Background:
• Marital status:
• Head of the Household:
• Main household occupation:
• Total household members (M/F):
• Type of household: Nuclear/Joint/Extended/Others
• Household annual income:
Name of family members Relation with the respondent Age Education Occupation
10. Religion:
• Hindu
• Muslim
• Christian
• Buddhist
• Sikh
• Other
11. Caste:
• SC
31
• ST
• OBC
• General
• Other
12. Which of the following ID documents do you have?
• Bank Account
• Jan Dhan Account
• Ration Card
• Voter Card
• Aadhar Card
• Other (please specify)
13. Native Place:
14. How many years have you been living in the current place?
• None
• Less than 5
• 5-10 years
• 10-15 years
• More than 15
II) HOUSING/ TIME-USE:
15. What form of housing do you live in?
• Kuchha
• semi-pakka
• rented room/house
• Community housing
• Own house
16. Do you share the rented accommodation with others who are not family members?
17. How many rooms are there?
18. How many bathrooms are there?
19. Do you have access to water for drinking and cleaning?
20. Do you have a rent agreement?
21. Did you have to vacate housing? If yes, what were the reasons?
22. What were the assets the household had?
• TV
• refrigerator
• bicycle
• motorbike
• mobile or smartphone
• AC or cooler
• pump set
• inverter
• land or plot in the city or native place
• Any other
32
23. Do you have a ration card? Which color?
24. Do you avail PDS benefits according to your ration card?
25. No. of hours spent on:
• paid work:
• skill enhancement or learning:
• unpaid work:
• personal care:
• leisure:
• other:
III) EMPLOYMENT
26. Nature of Employment (SELF):
• Primary Sector (Major time in a year) (1-Agriculture, 2- Manufacturing/ allied industry, 3-
Construction, 4-Service)
• Secondary Sector (Minor time in a year) (1-Agriculture, 2 Manufacturing/allied industry, 3-
Construction, 4- Service)
27. Type of Occupation (SELF):
• Construction Labour
• Brick Kilns
• Domestic Labour
• Street Vendor
• Waste Recycler
• Agriculture Labour
• Sugarcane Harvesters
• IMCL (Indian Made commercial Liquor) Factory Worker
• Other Industrial Workers
• Others (please specify)
28. Nature of Employment (PARTNER):
• Primary Sector (Major time in a year) (1-Agriculture, 2- Manufacturing/ allied industry, 3-
Construction, 4-Service)
• Secondary Sector (Minor time in a year) (1-Agriculture, 2 Manufacturing/allied industry, 3-
Construction, 4- Service)
29. Type of Occupation (PARTNER):
• Construction Labour
• Brick Kilns
• Domestic Labour
• Street Vendor
• Waste Recycler
• Agriculture Labour
• Sugarcane Harvesters
• IMCL (Indian Made commercial Liquor) Factory Worker
• Other Industrial Workers
33
• Others (please specify)
30. Employment Status:
• Pre-Covid-19 (January-March 2020)- Employed/Unemployed
• During Covid-19 first wave (April-May 2020)- Employed/Unemployed
• After Covid-19 first wave (August-October 2020)- Employed/Unemployed
• During Covid-19 second wave (April-June 2021)- Employed/Unemployed
31. Partner’s Employment Status:
• Pre-Covid-19 (January-March 2020)- Employed/Unemployed
• During Covid-19 first wave (April-May 2020)- Employed/Unemployed
• After Covid-19 first wave (August-October 2020)- Employed/Unemployed
• During Covid-19 second wave (April-June 2021)- Employed/Unemployed
32. Are you employed through a contractor?
33. Do you have a written contract?
34. Do you receive regular wages?
35. If yes, who pays your wages- Contractor or employer?
36. What is your annual household income, including primary and secondary employment?
37. Method of payment:
• regular monthly salary
• regular weekly payment
• daily payment
• piece rate payment
• others
38. Were you able to save some money?
39. If you were a migrant, were you able to send some remittances home? If yes, how much?
40. Did you buy any insurance policy/plans?
41. Availability of social security benefits
• PF
• Health
• Maternity Benefits
• Pension
• None
42. Have you received wages for the work you did before the lockdown began?
• Yes
• No, but sure of receiving it
• No, and unsure that it will be received
43. Has your employer paid salaries for the duration of the lockdown?
• Yes
• Yes, but partial (till when)
• No
44. How has the employer behaved with you during the lockdown period?
• Job assurance post lockdown
• Has provided other support but no job assurance
34
• No support or job assurance
• No contact
• Other (please specify)
45. What additional skills do you possess?
stitching/tailoring, grooming, cooking, technician, driving, any crafts, any others
46. What additional skills do your family members possess?
stitching/tailoring, grooming, cooking, technician, driving, any crafts, any others
47. While in an economic crisis, did you look for any alternate livelihood options?
48. While in an economic crisis, did your family members look for any alternate livelihood options?
IV) DIGITAL LITERACY
49. Do you have a personal phone?
50. If not, do you share it with someone?
51. Who do you share it with?
52. Is it a smartphone?
53. What do you mostly use the mobile phone for (Rate 0-5)?
• Entertainment
• Communication
• Learning
• Financial Transaction
• Employment
54. Do you use social networking apps?
55. Do you know about the following platforms?
• YouTube
• Telegram
• Paytm/ Google Pay/ Phone Pay
• Yes Madam
• Uber/ Ola
• Google Maps
• Just Dial
• Mahila E-Haat
• Swayam
• Other
56. Which of the above have you used?
57. How would you rate the following from 1 to 5 (1=lowest, 5=highest)?
• Ability to use smartphones?
• Making and receiving phone calls?
• Internet literacy (the ability to use the Internet)?
• Typing skills?
35
• Web search skills?
• Computer literacy (the ability to use the computer)?
58. Yes/No
• Can you take and edit digital photos?
• Can you record and edit digital sounds?
• Can you record and edit digital videos?
• Can you download apps?
59. Do you know about the employment opportunities available with the help of digital tools?
60. If yes, what are they?
61. Do you know about platforms that can help you develop/enhance your skills?
62. If yes, list them:
63. Do you know about the Digital Saksharta Abhiyan (DISHA) or National Digital Literacy Mission (NDLM)
Scheme?
64. If yes, from where did you hear about it?
65. Do you avail benefits from the scheme?
66. Do you avail economic benefits from any other scheme?
67. Do you receive support from any organizations while accessing digital technology?
68. If yes, then what kind of support?
69. Do you receive support from any organizations to enhance or learn new skills?
70. If yes, then what kind of support?
71. Do you want to improve your skills to use internet and smartphones efficiently?
72. What are the challenges you faced while accessing digital tools?
• Lack of time
• Lack of skills
• Expensive
• Lack of information
• Lack of internet connectivity
• Lack of network coverage
• Electricity challenges
• Shared with other members
• Not allowed to use internet by family members
• Difficulty in reading
• Difficulty in typing
• Nobody to teach or help me to use mobile internet
• Unsafe
• Not enough in my own language on the internet
• Lack of relevant content
• Others
73. How did you cope with the above challenges? Give one
36
10. References Gurumurthy, A., Chami, N., & Thomas, S. (2016). Unpacking Digital India: A Feminist Commentary on
Policy Agendas in the Digital Moment. Journal of Information Policy, 6, 371-402.
doi:10.5325/jinfopoli.6.2016.0371
Steyaert, J., & Gould, N. (2009). Social Work and the Changing Face of the Digital Divide. The British
Journal of Social Work, 39(4), 740-753. Retrieved July 25, 2021, from
http://www.jstor.org/stable/23724327
Sylvia E. Korupp, & Szydlik, M. (2005). Causes and Trends of the Digital Divide. European Sociological
Review, 21(4), 409-422. Retrieved July 25, 2021, from http://www.jstor.org/stable/4621219
Pollitzer, E. (2018). CREATING A BETTER FUTURE: FOUR SCENARIOS FOR HOW DIGITAL
TECHNOLOGIES COULD CHANGE THE WORLD. Journal of International Affairs, 72(1), 75-90.
Retrieved July 25, 2021, from https://www.jstor.org/stable/26588344
Amy Bach, Gwen Shaffer, & Todd Wolfson. (2013). Digital Human Capital: Developing a Framework for
Understanding the Economic Impact of Digital Exclusion in Low-Income Communities. Journal of
Information Policy, 3, 247-266. doi:10.5325/jinfopoli.3.2013.0247
Calderón-Gómez, D., Casas-Mas, B., Urraco-Solanilla, M., & Revilla, J. (2020). The labour digital divide:
Digital dimensions of labour market segmentation. Work Organisation, Labour & Globalisation, 14(2), 7-
30. doi:10.13169/workorgalaboglob.14.2.0007
Ursula Huws. (2012). The reproduction of difference: Gender and the global division of labour. Work
Organisation, Labour & Globalisation, 6(1), 1-10. doi:10.13169/workorgalaboglob.6.1.0001
Intel, Dalberg (2012). Women and the Web. Bridging the Internet and Creating New Global Opportunities
in Low and Middle Income Countries.
O’Donnell, M., Buvinic, M., Kenny, C., Bourgault, S., & Yang, G. (2021). (Rep.). Center for Global
Development. Retrieved July 25, 2021, from http://www.jstor.org/stable/resrep30894
O’Donnell, M., Buvinic, M., Bourgault, S., & Webster, B. (2021). (Rep.). Center for Global Development.
Retrieved July 25, 2021, from http://www.jstor.org/stable/resrep30893
Banzhaf, S., Ma, L., & Timmins, C. (2019). Environmental Justice: The Economics of Race, Place, and
Pollution. The Journal of Economic Perspectives, 33(1), 185-208. Retrieved August 30, 2021, from
https://www.jstor.org/stable/26566983
OECD (2021), "Time Use", OECD Social and Welfare Statistics (database),
https://doi.org/10.1787/675ecc4a-en (accessed on 23 August 2021).
37
Sorgner, A., E. Bode and C. Krieger-Boden (2017): The Effects of Digitalization for Gender Equality in
the G20 Economies, Women 20 study.
Global Compact Network India and Deloitte. (2019). Opportunity or Challenge? Empowering women and
girls in India for the Fourth Industrial Revolution. Retrieved from
https://www2.deloitte.com/content/dam/Deloitte/in/Documents/about-deloitte/UNGCNI_black_final v6
web high res.pdf
McKinsey Global Institute. (2019). Digital India: Technology to transform a connected nation. Retrieved
from
https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insight
s/digital%20india%20technology%20to%20transform%20a%20connected%20nation/mgi-digital-india-
report-april-2019.pdf
Intellecap. (2018). Digitizing Rural Value Chains in India: An Assessment of High Potential Opportunities
to Increase Women’s Economic Empowerment. USAID. Retrieved from http://intellecap.com/wp-
content/uploads/2018/10/Digitizing-Rural-Value-Chains-in-India_Intellecap-Report.pdf
Sen, Sesa (2020): “COVID-19 Relief Package: Street Vendors Seek Cash Transfers, Say They Have No
Confidence to Borrow,” Indian Express, 14 May,
https://www.newindianexpress.com/business/2020/may/14/covid-19-relief-package-street-vendors-seek-
cash-transfers-say-they-have-no-confidence-to-borrow-2143430.html.
Aajeevika Bureau. (2020). The Perils of being poor in the age of COVID19: A report on the situation of
South Rajasthan Migrant workers after the lockdown.
Global Compact Network India & Deloitte. (2019). Opportunity or Challenge? Empowering women and
girls in India for the Fourth Industrial Revolution.
https://www2.deloitte.com/content/dam/Deloitte/in/Documents/about-
deloitte/UNGCNI_black_final%20v6%20web%20high%20res.pdf
The UN Broadband Commission for Sustainable Development. (2017). Working Group on the Digital
Gender Divide Recommendations for action: bridging the gender gap in Internet and broadband
access and use.
IWWAGE. (2020). Generating Female Employment through Public Employment: A Scoping Paper.
UN Women, SEWA, & Sattva Consulting. (2020). Understanding the impact of digital assets on women in
the informal service sector.