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Was WWII Red Army a Meritocracy? Evgeny Finkel, Johns Hopkins SAIS David Szakonyi, George Washington University

Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

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Page 1: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Was WWII Red Army a Meritocracy? Evgeny Finkel, Johns Hopkins SAIS

David Szakonyi, George Washington University

Page 2: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Data and Questions

• Was there ethnic discrimination in the WWII Red Army?

• Was there politically motivated intra-Russian/Slavic discrimination based on perceived origin or loyalty to the regime?

Page 3: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Databases

• Individual soldiers, N: ~23 million• FIO, birthdate, birthplace (GIS), draft location, rank, unit, outcome (death,

decommission, etc.)

• Units: ~14,000• Type, commanders, place in order of battle, geographic coordinates

• Commanding Officers (Regiment level and higher): ~6,000• Biographical details

• Awards: ~17 million (given to ~8 million soldiers)• Year, type, awardee details

Page 4: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Issues and Problems

Page 5: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Coding Ethnicity

Three-part approach using first, patronymic and last names

1. Algorithm based on ЗАКС data (API run by Ivan Begtin)- First, middle and last names

2. Мемориал data from Zhukov and Talibova (2018)- Identify 100 most common last name per ethnicity

3. Last name окончание coding- Georgians: -швили, -дзе, -ава, -ия, -иани- Armenians: -ян

Page 6: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Most Common Last Names Per Ethnicity

1 Coding Ethnicity

• Using an API algorithm based on first, middle and last names

• Selecting the top 100 most common last names for each ethnicity in the Memorial database

• Simple last name suffixes for Georgian and Armenian

2 Results

• I subset the sample to soldiers that had complete name, birth year, and год призыва (the latter isimportant to uniquely identify people). We lose about 30% of the sample, but I think this is moredefensible. Also, including the Rank and Award YearFE causes that sample to drop even further.

• Table 5 shows a selection model into winning a prestigious award (one of the awards in Table 3 versuswinning a participation medal. I code RepublicFE based on the место призыва and FrontFE based onwhether their division had information on a specific Front (hence the loss of sample size).

• Table 6 is similar to before with a between award categories as denoted by the column headers (key inTable 3). This sample includes multiple awards per person with errors clustered on individual person,and is subset to only those who won prestigious awards.

• Table ?? just takes the best award won by each person and compares between categories, subsettingto only those who won prestigious awards.

Table 1: Top 10 Names by Ethnicity

Slavic Jewish Armenian German Georgian Polish Tatar / Central AsianИванов Абрамов Григорьян Гинзбург Варава Казимиров АкимовКузнецов Наумов Саркисян Гринберг Майсурадзе Савицкий ИбрагимовСмирнов Коган Петросян Розенберг Ломидзе Федорович ХасановПопов Левин Акопян Гольдберг Капанадзе Козловский АхмедовПетров Шапиро Арутюнян Рапопорт Долидзе Павлович АхметовВасильев Соломонов Григорян Гольденберг Георгадзе Новицкий БулатовКозлов Гуревич Оганесян Шмидт Гоголадзе Соколовский СулеймановВолков Аронов Хачатурян Штейнберг Гелашвили Янковский КасимовНовиков Рабинович Арутюнов Розенфельд Чхаидзе Гулевич МаликовСоколов Давидов Троян Айзенберг Беридзе Каминский Рахманов

1

Page 7: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Awards Per Ethnic Group

Table 2: Descriptive Statistics - Ethnicities

Ethnicity N PercTotal UniquePeople AvgAge AvgMilitaryExpJewish 195,082 1.70 152,485 30.30 2.90Slavic 10,989,825 95.80 8,278,864 28.50 2.70Georgian 53,089 0.50 46,344 29.00 2.90Armenian 77,152 0.70 67,556 28.40 2.80Tatar / Central Asian 137,850 1.20 115,381 28.70 2.60Polish 4767 0.00 3925 28.70 2.20German 10,465 0.10 8,300 28.90 3.10

Table 3: Ranking Awards

Abbrev. Award Name N1 HSU Герой Советского Союза 220072 OL Орден Ленина 135883 ORS Орден Красной Звезды 27202444 ORB Орден Красного Знамени 2362355 OFW I Орден Отечественной Войны I степени 3124596 OFW II Орден Отечественной Войны II Степени 9281747 OG I Орден Славы I Степени 27138 OG II Орден Славы II Степени 446089 OG III Орден Славы III Степени 872553

Table 4: Selection into Prestigious Award: Ethnicity, Best Award

(1) (2) (3) (4)Armenian −0.013 −0.015∗∗ −0.008∗ 0.013∗∗

(0.009) (0.007) (0.004) (0.005)

Georgian −0.015∗ −0.019∗∗∗ −0.011∗∗ −0.010∗∗∗(0.009) (0.007) (0.005) (0.004)

German −0.024∗∗∗ −0.019∗∗ −0.013 0.002(0.008) (0.008) (0.009) (0.010)

Jewish −0.017∗∗∗ −0.012∗∗∗ −0.008∗∗∗ −0.005(0.003) (0.003) (0.002) (0.004)

Polish −0.024∗∗∗ −0.013∗∗ 0.003 0.003(0.005) (0.007) (0.007) (0.008)

Tatar / Central Asian −0.009∗∗∗ −0.011∗∗∗ −0.013∗∗∗ −0.014∗∗∗(0.002) (0.002) (0.001) (0.002)

Age (logged) −0.043∗∗∗ −0.043∗∗∗ −0.042∗∗∗(0.005) (0.006) (0.004)

Military Experience 0.016∗∗∗ 0.017∗∗∗ 0.017∗∗∗(0.003) (0.003) (0.003)

Rank FE Yes Yes Yes YesAward Year FE Yes Yes Yes YesRepublic FE No No Yes YesFront FE No No No YesObservations 6,247,545 6,236,956 5,771,016 2,819,864R2 0.264 0.267 0.259 0.289

*** p<0.01, ** p<0.05, * p<0.1

2

Page 8: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Coding Awards and Model Specifications

• Selection Into Awards• Comparing personal

decorations and campaign medals

• Comparing Between Categories• Taking advantage of

classification differences within “prestigious” awards

Controlling for age, experience (years in military), rank, award year, republic (birthplace), front

Table 2: Descriptive Statistics - Ethnicities

Ethnicity N PercTotal UniquePeople AvgAge AvgMilitaryExpJewish 195,082 1.70 152,485 30.30 2.90Slavic 10,989,825 95.80 8,278,864 28.50 2.70Georgian 53,089 0.50 46,344 29.00 2.90Armenian 77,152 0.70 67,556 28.40 2.80Tatar / Central Asian 137,850 1.20 115,381 28.70 2.60Polish 4767 0.00 3925 28.70 2.20German 10,465 0.10 8,300 28.90 3.10

Table 3: Ranking Awards

Abbrev. Award Name N1 HSU Герой Советского Союза 220072 OL Орден Ленина 135883 ORS Орден Красной Звезды 27202444 ORB Орден Красного Знамени 2362355 OFW I Орден Отечественной Войны I степени 3124596 OFW II Орден Отечественной Войны II Степени 9281747 OG I Орден Славы I Степени 27138 OG II Орден Славы II Степени 446089 OG III Орден Славы III Степени 872553

Table 4: Selection into Prestigious Award: Ethnicity, Best Award

(1) (2) (3) (4)Armenian −0.013 −0.015∗∗ −0.008∗ 0.013∗∗

(0.009) (0.007) (0.004) (0.005)

Georgian −0.015∗ −0.019∗∗∗ −0.011∗∗ −0.010∗∗∗(0.009) (0.007) (0.005) (0.004)

German −0.024∗∗∗ −0.019∗∗ −0.013 0.002(0.008) (0.008) (0.009) (0.010)

Jewish −0.017∗∗∗ −0.012∗∗∗ −0.008∗∗∗ −0.005(0.003) (0.003) (0.002) (0.004)

Polish −0.024∗∗∗ −0.013∗∗ 0.003 0.003(0.005) (0.007) (0.007) (0.008)

Tatar / Central Asian −0.009∗∗∗ −0.011∗∗∗ −0.013∗∗∗ −0.014∗∗∗(0.002) (0.002) (0.001) (0.002)

Age (logged) −0.043∗∗∗ −0.043∗∗∗ −0.042∗∗∗(0.005) (0.006) (0.004)

Military Experience 0.016∗∗∗ 0.017∗∗∗ 0.017∗∗∗(0.003) (0.003) (0.003)

Rank FE Yes Yes Yes YesAward Year FE Yes Yes Yes YesRepublic FE No No Yes YesFront FE No No No YesObservations 6,247,545 6,236,956 5,771,016 2,819,864R2 0.264 0.267 0.259 0.289

*** p<0.01, ** p<0.05, * p<0.1

2

Page 9: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Table 2: Descriptive Statistics - Ethnicities

Ethnicity N PercTotal UniquePeople AvgAge AvgMilitaryExpJewish 195,082 1.70 152,485 30.30 2.90Slavic 10,989,825 95.80 8,278,864 28.50 2.70Georgian 53,089 0.50 46,344 29.00 2.90Armenian 77,152 0.70 67,556 28.40 2.80Tatar / Central Asian 137,850 1.20 115,381 28.70 2.60Polish 4767 0.00 3925 28.70 2.20German 10,465 0.10 8,300 28.90 3.10

Table 3: Ranking Awards

Abbrev. Award Name N1 HSU Герой Советского Союза 220072 OL Орден Ленина 135883 ORS Орден Красной Звезды 27202444 ORB Орден Красного Знамени 2362355 OFW I Орден Отечественной Войны I степени 3124596 OFW II Орден Отечественной Войны II Степени 9281747 OG I Орден Славы I Степени 27138 OG II Орден Славы II Степени 446089 OG III Орден Славы III Степени 872553

Table 4: Selection into Prestigious Award: Ethnicity, Best Award

(1) (2) (3) (4)Armenian −0.013 −0.015∗∗ −0.008∗ 0.013∗∗

(0.009) (0.007) (0.004) (0.005)

Georgian −0.015∗ −0.019∗∗∗ −0.011∗∗ −0.010∗∗∗(0.009) (0.007) (0.005) (0.004)

German −0.024∗∗∗ −0.019∗∗ −0.013 0.002(0.008) (0.008) (0.009) (0.010)

Jewish −0.017∗∗∗ −0.012∗∗∗ −0.008∗∗∗ −0.005(0.003) (0.003) (0.002) (0.004)

Polish −0.024∗∗∗ −0.013∗∗ 0.003 0.003(0.005) (0.007) (0.007) (0.008)

Tatar / Central Asian −0.009∗∗∗ −0.011∗∗∗ −0.013∗∗∗ −0.014∗∗∗(0.002) (0.002) (0.001) (0.002)

Age (logged) −0.043∗∗∗ −0.043∗∗∗ −0.042∗∗∗(0.005) (0.006) (0.004)

Military Experience 0.016∗∗∗ 0.017∗∗∗ 0.017∗∗∗(0.003) (0.003) (0.003)

Rank FE Yes Yes Yes YesAward Year FE Yes Yes Yes YesRepublic FE No No Yes YesFront FE No No No YesObservations 6,247,545 6,236,956 5,771,016 2,819,864R2 0.264 0.267 0.259 0.289

*** p<0.01, ** p<0.05, * p<0.1

2

Page 10: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Table 5: Selection into Prestigious Award, Interaction

(1) (2) (3)Military Experience 0.016∗∗∗ 0.017∗∗∗ 0.017∗∗∗

(0.003) (0.003) (0.003)

Armenian −0.019∗∗ −0.015∗∗ −0.012(0.009) (0.006) (0.007)

Georgian −0.014 −0.011 −0.011∗(0.011) (0.009) (0.006)

German −0.009 −0.002 0.015(0.012) (0.014) (0.014)

Jewish −0.005 −0.002 −0.002(0.004) (0.003) (0.004)

Polish −0.008 0.014∗ 0.013(0.007) (0.008) (0.008)

Tatar / Central Asian −0.009∗∗∗ −0.012∗∗∗ −0.017∗∗∗(0.002) (0.002) (0.003)

Armenian * Experience 0.001 0.003 0.010∗∗(0.002) (0.002) (0.004)

Georgian * Experience −0.002 −0.00002 0.001(0.002) (0.002) (0.002)

German * Experience −0.004 −0.004 −0.005∗(0.002) (0.003) (0.003)

Jewish * Experience −0.002∗∗∗ −0.002∗∗∗ −0.001∗(0.001) (0.001) (0.001)

Polish * Experience −0.003 −0.006∗ −0.006(0.002) (0.003) (0.005)

Tatar / Central Asian * Experience −0.001 −0.001 0.001(0.001) (0.001) (0.001)

Rank, Award Year FE Yes Yes YesRepublic FE No No YesFront FE No No NoObservations 6,236,956 5,771,016 2,819,864R2 0.267 0.259 0.289

*** p<0.01, ** p<0.05, * p<0.1

3

Page 11: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Table 5: Between Categories

1 vs. 2 1 vs. 2-3 1-2 vs. 3-4 5 vs. 6 7-8 vs. 9(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Armenian −0.018 −0.006 0.0003 0.0002 0.0004 0.0004 0.011∗ 0.011∗ 0.003∗∗∗ 0.003∗∗∗(0.053) (0.051) (0.001) (0.001) (0.001) (0.001) (0.007) (0.007) (0.001) (0.001)

Georgian 0.079 0.083∗ 0.002∗∗ 0.002∗∗ 0.001 0.001 0.027∗∗∗ 0.028∗∗∗ 0.002∗∗ 0.002∗∗(0.048) (0.049) (0.001) (0.001) (0.001) (0.001) (0.006) (0.006) (0.001) (0.001)

German −0.237 −0.270∗ −0.003∗∗∗ −0.003∗∗∗ −0.004∗∗∗ −0.004∗∗∗ 0.009 0.010 −0.003∗ −0.003∗(0.153) (0.146) (0.001) (0.001) (0.001) (0.001) (0.017) (0.018) (0.002) (0.002)

Jewish −0.074∗∗ −0.072∗∗ −0.002∗∗∗ −0.001∗∗∗ −0.002∗∗∗ −0.001∗∗∗ −0.018∗∗∗ −0.016∗∗∗ −0.001∗∗∗ −0.001∗∗(0.034) (0.033) (0.0004) (0.0004) (0.001) (0.0005) (0.006) (0.005) (0.001) (0.001)

Polish 0.079 0.088 0.003 0.003 0.002 0.002 −0.027 −0.025 0.001 0.001(0.091) (0.085) (0.003) (0.003) (0.003) (0.003) (0.028) (0.028) (0.002) (0.002)

Tatar / Central Asian 0.026 0.031 0.0002 0.0002 −0.0002 −0.0001 −0.003 −0.003 0.002∗∗∗ 0.002∗∗∗(0.030) (0.031) (0.0004) (0.0004) (0.001) (0.001) (0.004) (0.004) (0.001) (0.001)

Age (logged) −0.230∗∗∗ −0.004∗∗∗ −0.005∗∗∗ −0.051∗∗∗ −0.004∗∗∗(0.055) (0.001) (0.001) (0.009) (0.001)

Military Experience −0.006∗∗∗ 0.00004 0.001∗∗∗ 0.003∗∗∗ 0.0003∗∗(0.002) (0.0001) (0.0002) (0.001) (0.0001)

Rank FE Yes Yes Yes Yes Yes Yes Yes Yes Yes YesAward Year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes YesObservations 10,490 10,488 1,826,834 1,824,726 1,946,072 1,943,905 551,463 550,706 3,750,010 3,742,345R2 0.245 0.256 0.020 0.021 0.021 0.021 0.065 0.066 0.011 0.011

*** p<0.01, ** p<0.05, * p<0.1

Table 6: Between Categories

HSU vs. OL HSU vs. OL/ORS HSU/OL vs. ORS/ORB OFW I vs. OFW II OG I/II vs. OG III(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)

Armenian −0.013 −0.002 0.0003 0.0002 0.001 0.001 0.007 0.007 0.003∗∗∗ 0.002∗∗∗(0.057) (0.056) (0.001) (0.001) (0.001) (0.001) (0.005) (0.005) (0.001) (0.001)

Georgian 0.083 0.087 0.002∗∗ 0.002∗∗ 0.002∗ 0.002∗ 0.025∗∗∗ 0.026∗∗∗ 0.002∗∗∗ 0.002∗∗∗(0.060) (0.060) (0.001) (0.001) (0.001) (0.001) (0.006) (0.006) (0.001) (0.001)

German −0.231 −0.263∗ −0.003∗∗∗ −0.003∗∗∗ −0.004∗∗∗ −0.004∗∗∗ −0.002 −0.001 −0.003∗∗∗ −0.004∗∗∗(0.156) (0.149) (0.001) (0.001) (0.001) (0.001) (0.012) (0.012) (0.001) (0.001)

Jewish −0.071∗∗ −0.069∗∗ −0.002∗∗∗ −0.001∗∗∗ −0.002∗∗∗ −0.001∗∗∗ −0.019∗∗∗ −0.016∗∗∗ −0.001∗∗∗ −0.001∗∗∗(0.035) (0.035) (0.0003) (0.0003) (0.0004) (0.0004) (0.003) (0.003) (0.0003) (0.0003)

Polish 0.085 0.094 0.003 0.003 0.001 0.002 −0.001 0.002 −0.001 −0.001(0.093) (0.087) (0.003) (0.003) (0.003) (0.003) (0.022) (0.022) (0.002) (0.002)

Tatar / Central Asian 0.027 0.032 0.0002 0.0002 −0.0001 −0.0001 −0.001 −0.00002 0.002∗∗∗ 0.002∗∗∗(0.041) (0.041) (0.0004) (0.0004) (0.0005) (0.0005) (0.004) (0.004) (0.0004) (0.0004)

Age (logged) −0.226∗∗∗ −0.004∗∗∗ −0.005∗∗∗ −0.070∗∗∗ −0.005∗∗∗(0.024) (0.0002) (0.0002) (0.002) (0.0001)

Military Experience −0.006∗∗∗ 0.00004 0.001∗∗∗ 0.003∗∗∗ 0.0004∗∗∗(0.001) (0.00003) (0.00004) (0.0002) (0.00003)

Rank FE Yes Yes Yes Yes Yes Yes Yes Yes Yes YesAward Year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes YesObservations 10,615 10,613 1,829,582 1,827,474 2,000,821 1,998,653 898,171 897,389 4,562,489 4,554,519R2 0.246 0.257 0.020 0.020 0.019 0.019 0.068 0.069 0.013 0.013

*** p<0.01, ** p<0.05, * p<0.1

3

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Coding Slavic Last Names

Examining within-ethnicity variation (Slavic) by coding last names according to:• Sacked • Tsarist• Repressed• Defectors• Revolutionary• Heroes

Table 5: Last Name Categories

Last Name Category NПавлов sacked 35895Романов tsarist 25348Жуков heroes 22400Власов defectors 18570Краснов tsarist 8434Еременко heroes 6504Зиновьев repressed 5718Ульянов revolutionary 5650Корнилов tsarist 4732Панфилов heroes 4339Ежов nkvd 3475Конев heroes 3272Каменев repressed 2560Рыков repressed 2205Василевский heroes 2074Матросов heroes 1886Строганов tsarist 1496Ворошилов revolutionary 1408Бухарин repressed 747Троцкий repressed 337Стаханов heroes 330Чапаев revolutionary 295Буденный sacked 240Ленин revolutionary 188Голицын tsarist 171Томский repressed 107Деникин tsarist 65Берия nkvd 64ягода nkvd 54юденич tsarist 39колчак tsarist 37дзержинский nkvd 23сталин revolutionary 19мехлис sacked 11рокоссовский heroes 5врангель tsarist 1

5

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Results Using Slavic Last Names

• Null effects from Selection into Awards analysis

• Null effects from Between Categories analysis

• Null effects from Between Categories analysis, breaking down within ranks

Page 14: Was WWII Red Army a Meritocracy? · 1. Algorithm based on ЗАКС data (API run by Ivan Begtin)-First, middle and last names 2. Мемориал data from Zhukov and Talibova (2018)

Main Takeaways

• Evidence of ethnic discrimination of some groups• Negative (Jews and German especially)• Mixed (Georgians: negative in selection into awards, positive in getting

prestigious awards)

• No evidence of origin and background driven discriminations among a core group (Russians/Slavs)• Next steps; data, analysis, questions• Any suggestions are welcomed

Thank You!

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Was WWII Red Army a Meritocracy? Evgeny Finkel, Johns Hopkins SAIS

David Szakonyi, George Washington University