Genes and the Fertility of Tibetan Women at High Altitude in Nepal National Science Foundation Grant...
-
Upload
irma-patterson -
Category
Documents
-
view
213 -
download
0
Transcript of Genes and the Fertility of Tibetan Women at High Altitude in Nepal National Science Foundation Grant...
Perpetuating Inequality through Education? RelativeWealth and Boarding School Attendance in Highland Nepal
Geoff ChildsWashington University
Genes and the Fertility of Tibetan Women at High Altitude in Nepal
National Science FoundationGrant No. BCS-1153911
CynthiaBeall
SiennaCraig
me
Nubri Tsum
Mus
tang
Location of Fieldwork Sites in Nepal
Data
• For women 40+– Spittle for DNA analysis.– Blood measurements (non-invasive).– Reproductive history survey.
• For all Households– Demographic and economic survey.– Relative wealth survey.
Geographical Coverage of Surveys2012: n=500 HHs, all villages 10,000ft +
Nubri ValleyTsum Valley
Nubri ValleyTsum Valley
Main Villages
Sama
Samdo
LhoChökhang
Nyilö
Nubri ValleyTsum Valley
Local Schools
Sama
Samdo
LhoChökhang
Nyilö
Local Educational Opportunities
• History of non-functional local school system in Nubri and Tsum.
• Primary schools in most villages (kg – 3rd), but not very effective.
• Boarding school in Sama (kg – 6th).
• Uneducated parents have strong desire for own kids to receive education.
0-45-9
10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-79
80+
8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8
Nubri & Tsum 2012
males (% of total population) females
age
grou
p
High fertility5.9 births/woman
(40-49 cohort)
0-4
5-9
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80+
8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8
Nubri & Tsum 2012males home
males away
females home
females away
males females
age
grou
p
72% 28% 28% 72%75% 25% 34% 66%
42% 58% 58% 42%
% In HH % Out of HH
Males1997 60.8% 39.2%2012 26.8% 73.2%
Females1997 88.8% 11.2%2012 33.1% 66.9%
• Large increase of males aged 10-19 living away from natal HHs (from 39% to 73%).
• Dramatic increase of females aged 10-19 living away from natal HHs (from 11% to 67%).
• Reduction of gender-based sending disparity.
People aged 10-19 by sex and residence
Where Are They Going?
Boarding Schools in Kathmandu (~ 50%)
Monasteries in India and Kathmandu (~ 50%)
Migration Decision-Making
“Here life is just putting a rope on your head and scratching the earth to make a living. If kids have education, whether they stay here or go outside, they can lead a less difficult life. When we went to Kathmandu we found out we are like lemba (deaf mutes).”
InternationalSponsorship as
MigrationOpportunity
School’s Perspective: Means-Tested Students
• Our students come from the high mountains of Nepal, from villages that have no electricity, no toilets, no sanitation, no telecommunications, no hospitals, no roads and no schools. Our kids come from villages that are 6 to 14 days' trek from the nearest road, villages that lie above 10,000 feet (3000 m). Getting word to and from the villages sometimes takes months, depending on weather conditions. . . .
• They are means-tested by virtue of their Himalayan origins.
minutessatellite
Questions
• Is there a connection between socioeconomic status and ability to attend boarding school?– Do kids who attend boarding schools in Kathmandu
(at $750 - $1,000 per yr) tend to come from relatively wealthy families?
• Does education reduce or amplify socioeconomic differences?
Anecdotal Evidence
• Comments by villagers suggest that wealthier HHs have easier time securing sponsorships through social networks.
• In-depth interviews reveal that some wealthy households with strong urban connections can easily find sponsorships.
Relative Wealth Survey
• Select three respondents who have knowledge of household wealth across the community.
• Ask each to:– Rank every HH from 1 (wealthy) to 5 (poor).– Ask for reasons behind each ranking.– Average the 3 rankings for each HH.
Methodological Shortcomings
• Can be difficult to get three knowledgeable and willing respondents.
• Egalitarian ethos: 3, 3, 3, “We’re all the same”.
• Reluctance to speak about others’ wealth (fear of social repercussions?)
Methodological Strengths
• Emic perspective on what constitutes wealthy versus poor.
• Works best in conjunction w/HH survey.• If you know land, cattle, income, household
composition, etc. ahead of time:– Paired comparisons to tease out further nuances
(“Why do you rank this HH 2 but this HH 4 when they have the same amount of land?”)
wealthy upper middle middle lower middle poor
Paired Comparison:Why did you rank Dorje’s and Tashi’s HHs the same
when Tashi has more land and animals?
Tashi
Dorje
Tashi’s HH Dorje’s HH
=
=
100 units of land 50 units of land20 yaks 10 yaks
Which Household is Wealthier?
Short Term: More assets (land & yaks)Long Term: No divisions through inheritance
Determinants of Wealth
• External Wealth (chi’i nor): land, animals, other visible assets.
• Internal Wealth (nang gi nor): jewelry, religious items, heirlooms.
• Demographic: household composition and labor force.
• Competence.
Determinants of Wealth
• Poorest (4-5)– Little land and cattle (poor before or too many
divisions among sons).– Inadequate labor force.– Phorang/Morang: divided assets and retired
(elderly) or solitary and impoverished.– Incompetent or alcoholic.
Determinants of Wealth
• Wealthiest (1-2)– Lots of land and cattle (chi’i nor).– Abundant gold and jewelry (nang gi nor).– Strong labor force (farming, herding, yartsa gunbu).– Adept at business (trade, hotel).– Salaried employment (govt, teacher).– HH member abroad (remittances).
yartsa (grass in summer)gunbu (bug in winter)
Ophiocordyceps Sinensis冬虫夏草
Rank (n) HH Members Land Bovines Income
(rupees)1 (45) 5.7 45.5 11.5 105,250
2 (88) 5.3 45.7 11.5 63,770
3 (102) 4.6 34.0 7.7 43,840
4 (58) 3.8 28.2 3.5 40,080
5 (50) 3.6 29.7 2.8 54,230
HH Wealth Ranking Correlations (2012)$1 = 85 rupees
Slight Mismatch?
• Some poor households (little land, few bovines) actually have considerable income.– Man from Tibet: no land, few animals, but teacher’s
salary, portering wages, yartsa gunbu income.– Single Mom: yartsa gunbu income plus large
remittance from daughter.– Single Mom: little land, few animals, but support
from foreign patron to build hotel (high income).
Yartsa Gunbu Income Total Income % from Yartsa
Gunbu
Samdo 67,375 85,832 78.5
Sama 69,770 91,192 76.5
Lho 12,826 14,071 91.2
Chökhang 29,430 52,525 56.0
Nyilö 32,889 40,300 81.6
Mean HH Income by Village (rupees)
$1 = 85 rupees
Nubri ValleyTsum Valley
Mean Household Income: Relative Wealth by Village?
Sama91,200
Samdo85,800
Lho14,000 Chökhang
52,500
Nyilö40,300
Wealthy
MiddlePoor
Question 1• Do more kids from wealthier than from poorer
villages attend boarding school?
ageSama & Samdo
Chokhang & Nyilö Lho
5-9 30.6 41.2 16.2 10-14 46.1 44.4 29.5 15-19 26.2 32.1 27.1Total 34.5 38.6 23.5
Percent of Kids in Boarding School by Age
Question 2
• Within each village, do kids who attend boarding schools tend to come from relatively wealthier households?
• Method: compare HHs with kids in eligible age range (5-19) by various economic indicators.
• HHs without kids are poorer than those with kids.• HHs with kid in boarding school rank higher on
relative wealth scale and have more income (but not more land or bovines) than those with no kid in boarding school.
Relative Wealth Land Bovines Income
Kids 5-19, none in boarding (n=115) 3.2 43.9 10.4 66,788
Kids 5-19, 1 or more in boarding (n=98) 2.7 43.8 8.3 81,037
No kids 5-19 (n=143) 3.6 25.5 5.2 34,574
Total (n=356) 3.2 36.4 7.7 57,654
Village Kid in Boarding
Relative Wealth Land Bovines Income
Samdono 3.2 11.8 4.0 84,267yes 2.8 23.3 6.7 104,945
Samano 3.1 46.2 14.8 115,525yes 2.7 41.0 11.6 158,417
Lhono 3.1 47.8 7.0 16,872yes 2.9 51.0 7.4 17,776
Chokhangno 3.3 32.3 4.1 46,462yes 2.3 52.9 5.8 84,256
Nyilöno 3.4 40.6 13.0 32,000yes 2.4 54.4 11.9 44,756
Social Networks and Sponsorship• I happen to know a lady at [school name]. I told her
that I wanted to request my son’s admission and she said I shouldn’t worry as she knows the director quite well. So the next day she helped me speak to the director and the director gave her approval. She asked how I am going to pay for the fees. I agreed to pay for the fees for one year, despite being a poor farmer, and requested her to find a sponsorship. Within 8 months she found a sponsor for my child.
Migmar, relatively wealthy with salary, good land, bovines, etc.
Questions• Do relatively wealthy people have stronger
urban social networks that facilitate movement of kids into boarding schools?
• Are more kids from relatively poor families sent to monasteries rather than boarding schools?
• Are contemporary trends intensifying existing socioeconomic disparities?
• What new disparities will emerge?– eg., those who go away versus those who stay put.
Layers of Inequality
Buddhist Highlanders Other Hindus Brahmins
Lho Chökhang/Nyilö Sama/Samdo
Relatively Poor Relatively Wealthy
Low STATUS HighSmal
ler
U
NIT
OF
ANAL
YTIS
L
arge
r
NATION
NUBRI& TSUM
Blacksmith Commoner LamaVILLAGE