Assignment #2: Employing machine learning to introduce the complexity of unemployment and statistical underrepresentation for the disabled population in Southeast Asia

Word Count: 2064

Special education is seen as a luxury in developing countries. Many countries struggle to provide equal education among genders, so educating the mentally and physically disabled is often pushed aside for gender equality. Another prominent struggle in the disabled population, that both developed and developing countries experience, is the lack of data quantifying the population itself. It is nearly impossible to spark political and local momentum to remove unfreedoms in education if governments and the public do not know the amount of people that are actually enduring the unfreedoms. The disabled population in developing countries are not only underrepresented in data, but they are also innately ostracized in communities, without teachers, thus, uneducated, and unemployed. Disabled people in Southeast Asia are especially vulnerable due to the main industries in the region and their incompatibility with the skills of the disabled.

Amartya Sen argues that development is the expansion of freedoms. Therefore, the lack of freedom, what Sen calls “unfreedoms,” are hindrances to development that first must be removed in order for a country, community, or individual to experience development growth. Having limited or no access to an education is an unfreedom that leads to other unfreedoms such as unemployment. In Southeast Asia, a lack of freedom in the disabled community hurts the development of the region as a whole as those who are disabled are unable to contribute to the economy, thus the GDP, as they are uneducated.

Many countries have data on their population in an educational system under the age of 21, but there is little to no distinction for disabled children, especially in developing countries. Even in the United Kingdom, as seen in “What Can Analytics Contribute to Accessibility in e-Learning Systems and to Disabled Students’ Learning?” from Assignment 1 by Cooper, Ferguson, and Wolff, who used educational evaluations to survey a student population, there is a plethora of data on general education students by “age, gender, ethnicity, family background, and study habits,” yet there is no differentiation in the data for students with disabilities. This underrepresentation is even more severe in developing countries where it is extremely difficult for a disabled person to have access to an education or a job, where statistics are often collected through surveys and censuses. The governments are unaware of how many disabled people are affected by their education systems, so here is little to no motivation to prioritize let alone solve this issue.

In general, people with disabilities “experience greater employment opportunities in larger organizations, and experience more difficulties in obtaining employment in medium-sized and smaller ones” (Lengnick-Hall et al.) This unintentional discrimination is due to the scarcity of “trained staff to manage work accommodations, limited opportunities for shifting workers with disabilities into other jobs in the company, and often lack generous health or disability benefits” (Lengnick-Hall et al.) Specific industries that unintentionally exclude people with disabilities tend to be in “low-growth sectors like agriculture, mining, construction, and manufacturing” (Lengnick-Hall et al.) In South East Asia, “small factories dominate, both in terms of the number of companies and the number of workers employed. Agricultural processing is most important in virtually all nations” (Leinbach & Frederick, 2018). This makes living in this region very disheartening for an ambitious disabled person seeking employment as the economy alone hinders their success- even if they are educated. Due to the lack of data involving the disabled population in general, firms in Southeast Asia lack initiative to enforce inclusive hiring. The government does nott incentivize helping lift the disabled community out of unemployment and many firms are unaware of the issue in general.

Recently, there has been an increase in the special education classroom student-teacher ratio in both developing and developed countries. This is because disabilities are becoming more common. To combat this, governments that have the time and resources to address this issue have been seeking approval for increased funding- which are often denied. Even if funding is approved and staff training is paid for, many regular education teachers would be forced to pivot to a career in special education. This popular solution is costly, slow, and unfortunate for both the teachers and students by assigning staff to special education even if they do not have the emotional patience or passion for it. Many countries view an increase in funding as the only solution to the student to teacher ratio, so developing countries are practically helpless if money is the solution to the problem. Thus, if they recognize the problem and seek a solution that is not financially stressful, they will force regular education teachers to pivot careers without the proper training.

In developing countries in Southeast Asia, access to special education is similar to the education conditions in Lebanon that were addressed in Assignment 1 with the source “ I Would Like to Go to School” by Human Rights Watch where the researchers employed systematic samples to collect their data in Lebanese districts. In South East Asia, similar to the conditions in Lebanon, disabled children and their families struggle to find a school. Schools can afford to deny disabled children admittance because the non-discriminatory policies are not enforced. These children are not the priority for equal education right now because many developing countries are still struggling to integrate girls into their school systems. People with disabilities may be denied an education for a variety of reasons- lack of government resistance to discrimination, no wheelchair accessibility, the social stigma assigned to inclusive learning with diabled children, or a lack of teachers with special education training.

First, a government might not know the sheer size of the disabled population due to a paucity of data, leading to a lack of inclusive policies and proper funding. This is not necessarily because the government is corrupt or malicious, but rather, the data that is necessary to inspire inclusivity is ultimately lacking. They cannot solve a problem that they do not know about in the first place, which is why collecting data on neurodiverse populations is so important, especially in developing countries where education for regular education students is not always easily accessible.

Second, creating an inclusive physical environment is very costly. The schools need wheelchair accessible transportation and curb cuts in order to get the students to the school safely, and that is only the beginning. There needs to be even more equipment inside the school, such as elevators and wheelchair ramps. Then, as the students reach the learning environment, there is a great need for braille resources, wheelchair-friendly desks, iPads for the mute, and so on. Many students will need extra staff members compared to the typical general education student, as they have unique needs. This could require sign language interpreters, personal attendants, and more medical professionals than only a school nurse. The salaries of all of these workers are increased expenses that the government would have to pay in order to create the bare minimum of an education system. Even with all of these supplies, the special education program might not even be successful or academically progressive for the students.

Third, in developing countries there are often few initiatives to increase public knowledge on disabled people. Many parents, uneducated on the disabled population and the benefits of interacting with physically and mentally disabled students, do not want their children being in the same school as them. Even if they are okay with their children attending an inclusive school, they might not be accepting of an inclusive classroom where disabled and non-disabled students are learning together from the same teacher in the same classroom. For this reason, many schools deny disabled children admittance, simply because they would lose so many regular education students. This is especially prominent in private schools where tuition is pricey and a loss of one student can significantly influence the institution’s financial situation.

Fourth, in order to integrate disabled children into any education system, with inclusive or exclusive learning, there needs to be staff that is trained to teach disabled children. Some schools might train their regular education teachers and have them teach in regular education and special education, whereas others might hire a whole new teacher for the special education program only. Either way, this is a costly investment in the disabled population. Special education teachers typically do not make as high of salaries as regular education teachers, so there is little financial incentive to go into special education. In addition, the field of special education requires lots of patience and warmth that is sometimes exhausted after spending lots of time in the same job. Many special education teachers “burnout” after years of being accommodating, loving, and accepting to their students at school as well as their own children at home. Unfortunately, people often associate special education with professional babysitting, which is another deterrent for becoming a special education teacher. These are all contributing factors to the increasing student to teacher ration in special education programs, in addition to the current upward trend in how many people are born with disabilities.

Even schools that allow disabled students to attend require “special charges” to compensate for the child’s disabilities (Human Rights Watch). The families are often under financial stress and cannot afford to pay these “special charges” due to the amount of medical bills they have to pay for their disabled child. There are almost no undergraduate scholarships for children with disabilities, as most are for high school graduates entering higher education, but many disabled people do not make it as far as graduating high school.

Uneducated people with disabilities have an even harder time finding jobs than educated disabled people. In South East Asia, where the local industries are not well-suited for the integration of disabled workers or the skill of diabled workers, being uneducated on top of that makes it nearly impossible to get a job. There is a lot of data on the type of industries that are prominent in Southeast Asia, so while we do not have a clear idea of how many disabled people are excluded from the workforce, we can predict that a high percentage of the population is unemployed simply due to the nature of the leading industries and firms.

In my opinion, it is most important to collect data on Southeast Asia’s disabled population. Educating the governments and the public on the prominence of disabiled people is a good start to simply raising awareness. From there, it would be useful to have an idea of how many disabled people are uneducated. Then, understanding how education affects employment in the disabled population is a clear representation of this development issue and can spark initiative.

So far in my research, I have gained a fuller understanding of the network of consequences that come with not having access to an education. This perspective aligns with Amartya Sen’s argument that freedoms are deeply interconnected and strengthen each other. While it is disheartening how a lack of education is so harmful to children with special needs, I am hopeful that society’s natural increase in technology is conducive to a solution. As technology increases it becomes more accessible, increasing communication. An increase in communication leads to an exchange of ideas and knowledge that is free to transact and does not depreciate. This will make it eventually easier for people with special needs to self-educate as best they can so that they are educated enough to participate in the economy, despite the government’s involvement. Machine learning is especially conducive to educating disabled students outside of a school as the student can effectively learn and progress academically without the assistance of another person.

While the lack of population data is an obvious gap in the literature that needs addressing, it is also important to educate people on how much the economy would improve if this section of the population were integrated into the workforce. This might incentivize firms to hire, governments to educate, and citizens to empathize. Data science reveals the severity and extension of the unfreedoms that are littered throughout the globe, allowing us to better understand and sometimes quantify human development. In order to grasp human development issues, we must recognize their complex nature and resist reducing development’s intricacy to a linear and simple phenomenon that can be fixed with a single, one-size fits all solution. We should create adaptive and dynamic solutions that can respond to crises, changes in economy, and social and political progressions.

Bibliography

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Disability at a Glance. (2015). Disability at a Glance 2015: STRENGTHENING EMPLOYMENT PROSPECTS FOR PERSONS WITH DISABILITIES IN ASIA AND THE PACIFIC, 14–19. https://doi.org/10.18356/0c1ea1f5-en https://www.unescap.org/sites/default/files/SDD%20Disability%20Glance%202015_Final.pdf.

Disability in the South­East Asia Region, 2013. (2013). http://origin.searo.who.int/entity/disabilities_injury_rehabilitation/topics/disabilityinsear2013.pdf.

Leinbach, T. R., & Frederick, W. H. (2018, July 13). South East Asia- Industry. https://www.britannica.com/place/Southeast-Asia/Industry.

Lengnick-Hall, M., Gaunt, P., & Brooks, A. Why Employers Don’t Hire People With Disabilities: A Survey of the Literature. https://www.cprf.org/studies/why-employers-dont-hire-people-with-disabilities-a-survey-of-the-literature/.

Persons with a Disability: Labor Force Characteristics News Release. (2020, February 26). https://www.bls.gov/news.release/pdf/disabl.pdf.

Phillips, K., Houtenville, A., Nzamubona, K., O’Neill, J., & Katz, E. (2020, June 3). 2020 Survey: Executive Summary. https://kesslerfoundation.org/researchcenter-employment-and-disability-researchemployment-and-disability-survey-2020/2020-survey.