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Slipping Past the Test: Exploring an Overlooked Loophole to Social
Advantage in Russia’s Educational System
RC28 Conference, Tilburg, May 28-31, 2015
Yuliya Kosyakova (EUI, Florence)
Gordey Yastrebov (HSE, Moscow; EUI, Florence)
Dmitriy Kurakin (HSE, Moscow)
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1. research question and the context of study
2. theory and hypotheses
3. data and method
4. some results
2
Structure
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• Persistent inequalities: MMI and EMI arguments (Raftery,
Hout 1993; Shavit, Blossfeld (Eds.) 1993; Lucas 2001)
• Whether social inequality is also effectively maintained,
because more advantaged families are also more
susceptible to loopholes offered within institutional
(educational) systems?
→ bypass strategies
3
Research Question
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Russia as a case study:
1. standardized test system:
• Unified State Exam (~ American SAT or German Abitur)
• obligatory to all students after 11 years of sec. gen. education
• major requirement to get in higher education
2. an institutional loophole to slip past the examination and
retain the opportunity to get into higher education through
secondary vocational track
• taken after 9 years of sec. gen. education
• after 3-4 years of studies allows enrolment in 2-3rd year of studies
in higher education
4
The Context of Russia’s
Educational System (1)
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• Before USE (before 2009):
– admission exams administered by VUZs
– requirements above the level provided by school curriculum
– either: exceptional academic record
– or: additional training beyond school
• faculties of pre-higher education training (FDPs)
• informal training with VUZ tutors
– intimate knowledge about the content of exams
– direct facilitation of admission process → → →
5
The Context of Russia’s
Educational System (2)
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→ → → inequality of opportunity:
• geographical inequality (proximity to VUZs)
• socioeconomic inequality (expenses, awareness)
• USE reform (2009):
– a remedy for the problem
– but: important maneuver overlooked!
• recognized by families and students
• FDPs → faculties for secondary vocational education
• SSUZs → agreements with VUZs to signal prospective enrolment
in higher education
6
The Context of Russia’s
Educational System (3)
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7
The Context of Russia’s
Educational System (4)
USE introduced nationwide
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General track preferences according
to social background:
– risk aversion theory (Breen, Goldthorpe 1997)
– rational choice arguments (Boudon 1974)
– primary effects vs secondary effects
H1: Children from more advantaged families are generally
more likely to choose academic track over vocational tracks
8
Theory & Hypotheses (1)
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Adjustment in situation of lower ability (‘second chance’):
– bypass strategy → to avoid formal screening of performance
– advantaged families: avoid (!) sec. voc. track at fear of status
demotion, but:
– bypass strategy triggered if the risks of USE failure are
especially high ← e.g. compensatory advantage (Bernardi 2012)
H2.1(weak): The propensity to opt for the bypass strategy is more sensitive to
ability among children from more advantaged social backgrounds
H2.2(strong): Children from more advantaged social backgrounds are more
likely to opt for the bypass strategy, particularly, when their ability is low
9
Theory & Hypotheses (2)
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Russian Panel Study of Trajectories
in Education and Careers (TrEC):
– Based on TIMSS 2011 stratified sample (Wave 0)
• 8th graders: 4,893 students in 210 schools in 42 regions
– Rounds:
• Wave 0 (TIMSS 2011, 8th gr.)
• Wave 1 (2012, 9th gr.)
• Wave 1.1 (PISA 2012, 9th gr.)
• Wave 2 (2013 10th gr., over with track choice)
10
Research Design: Data
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• Track choice (dependent):
1. Primary vocational
2. True secondary vocational
3. Secondary vocational as bypass (pseudo-vocational)
• proxied with VUZ choice (more accurate data is pending)
4. Academic
5. Drop-outs (negligible and almost impossible)
• Social background (independent):
– maximum education of parents:
1. higher (and above)
2. below higher (i.e. secondary vocational and below)
11
Research Design: Variables (1)
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• Prior ability (independent):
1. TIMSS scores in math and science (8th grade)
2. PISA scores in math, science and reading (9th grade)
• Controls:
– gender
– area of residence → to account for varying educational opportunities
1. rural areas
2. urban areas
3. major cities (Moscow and Saint-Petersburg)
12
Research Design: Variables (2)
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• Modeling strategy
– multinomial logistic regressions (all analyses weighted)
– interaction between main variables of interest
• Model setups
– H1: P(track choice) = f (ability, SB, gender, residence)
– H2: P(track choice) = f (ability, SB, ability × SB, gender, residence)
– focus on behavior of predicted probabilities (not effect sizes, but
exploration of the general pattern)
13
Research Design: Models
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H1: Children from more advantaged families are generally
more likely to choose academic track over vocational tracks
14
Results: H1
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15
Results: H1
• horizontal lines – unconditional (baseline) probabilities of corresponding track choice
• results for several measurements of ability plotted
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H1: Children from more advantaged families are generally
more likely to choose academic track over vocational tracks
SUPPORTED
16
Results: H1
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H2.1(weak): The propensity to opt for the bypass
strategy is more sensitive to ability among children
from more advantaged social backgrounds
H2.2(strong): Children from more advantaged social
backgrounds are more likely to opt for the bypass
strategy, particularly, when their ability is low
17
Results: H2
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• horizontal lines – unconditional (baseline) probabilities of corresponding track choice
• vertical lines – average ability score in corresponding track
• MIN and MAX values for ability score calculated within track for the more advantaged group 18
Results: H2 (math)
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• horizontal lines – unconditional (baseline) probabilities of corresponding track choice
• vertical lines – average ability score in corresponding track
• MIN and MAX values for ability score calculated within track for the more advantaged group 19
Results: H2 (science)
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• horizontal lines – unconditional (baseline) probabilities of corresponding track choice
• vertical lines – average ability score in corresponding track
• MIN and MAX values for ability score calculated within track for the more advantaged group
20
Results: H2 (reading)
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H2.1(weak): The propensity to opt for the bypass
strategy is more sensitive to ability among children
from more advantaged social backgrounds
H2.2(strong): Children from more advantaged social
backgrounds are more likely to opt for the bypass
strategy, particularly, when their ability is low
STRONGER VERSION SUPPORTED
21
Results: H2
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• Support for the stronger version of the ‘second chance’
hypothesis (H2.2):
– advantaged families recognize the opportunity of avoiding USE
through secondary vocational track
– and use it to provide their children an opportunity to retain
access to higher education even if their ability is low
– i.e. both families and institutions adapt so that reproduction of
inequality is always maintained to a certain degree
22
Preliminary Conclusions
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• Future steps
– drawing a more accurate distinction between true secondary
vocational track and the bypass strategy (institutional adaptation)
– distinguishing between former FDPs and SSUZs with
agreements (correct coding using data on actual enrolment)
23
Directions of Further Research
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24
Thank you for your attention!
Yuliya Kosyakova
Dmitriy Kurakin
Gordey Yastrebov*
* corresponding author:
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25
Descriptive Statistics (cont.)
Variable Mean SD Min Max N
PISA math 493.7 82.2 194.7 798.2 4,271
PISA science 490.6 78.2 233.0 730.0 4,271
PISA reading 476.1 83.9 170.0 722.3 4,271
TIMSS math 542.9 77.7 308.7 804.0 4,657
TIMSS science 545.6 72.5 266.3 803.5 4,657
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26
Descriptive Statistics (cat.)
Variable % N
Track choice
primary vocational 63.2 4,657
true secondary vocational 21.5 4,657
pseudo-vocational 7.3 4,657
academic 8.0 4,657
Education of parents
lower and middle 51.0 4,657
higher 49.0 4,657
Gender
boys 50.2 4,657
girls 49.8 4,657
Area of residence
rural areas 21.2 4,657
urban areas 69.7 4,657
Moscow & St. Petersburg 9.1 4,657