evals <- structure(list(course_id = 1:463, prof_id = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 16L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 21L, 21L, 21L, 21L, 21L, 21L, 22L, 23L, 23L, 23L, 23L, 23L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 25L, 25L, 26L, 26L, 26L, 26L, 26L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 28L, 28L, 28L, 28L, 29L, 29L, 29L, 29L, 30L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 32L, 32L, 32L, 33L, 33L, 33L, 33L, 33L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 35L, 35L, 35L, 36L, 36L, 36L, 36L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 37L, 23L, 23L, 23L, 38L, 38L, 38L, 38L, 38L, 38L, 38L, 38L, 39L, 40L, 40L, 40L, 40L, 40L, 41L, 41L, 41L, 41L, 42L, 42L, 42L, 42L, 43L, 43L, 43L, 44L, 44L, 44L, 44L, 45L, 45L, 45L, 46L, 47L, 47L, 47L, 48L, 48L, 48L, 48L, 48L, 48L, 48L, 49L, 49L, 49L, 49L, 49L, 49L, 49L, 49L, 49L, 49L, 49L, 49L, 49L, 50L, 50L, 50L, 50L, 50L, 50L, 51L, 51L, 51L, 51L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 53L, 53L, 53L, 53L, 53L, 53L, 54L, 54L, 54L, 55L, 55L, 55L, 56L, 56L, 57L, 57L, 58L, 58L, 58L, 58L, 58L, 58L, 58L, 58L, 58L, 58L, 59L, 59L, 60L, 60L, 60L, 61L, 62L, 63L, 63L, 64L, 64L, 64L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 66L, 66L, 66L, 66L, 66L, 66L, 67L, 67L, 68L, 68L, 68L, 69L, 70L, 70L, 70L, 70L, 70L, 70L, 70L, 70L, 70L, 71L, 71L, 71L, 71L, 71L, 71L, 71L, 71L, 71L, 71L, 72L, 72L, 72L, 72L, 72L, 72L, 73L, 73L, 73L, 73L, 73L, 74L, 74L, 74L, 74L, 75L, 75L, 76L, 76L, 77L, 77L, 77L, 77L, 77L, 77L, 78L, 78L, 78L, 78L, 79L, 79L, 79L, 80L, 80L, 80L, 80L, 81L, 81L, 81L, 81L, 82L, 82L, 82L, 82L, 82L, 82L, 82L, 82L, 82L, 82L, 82L, 83L, 83L, 83L, 83L, 83L, 84L, 84L, 84L, 84L, 84L, 85L, 85L, 85L, 85L, 85L, 85L, 85L, 85L, 86L, 86L, 86L, 87L, 87L, 88L, 88L, 88L, 88L, 88L, 88L, 88L, 89L, 89L, 89L, 90L, 90L, 91L, 91L, 91L, 92L, 92L, 92L, 92L, 92L, 92L, 92L, 93L, 93L, 93L, 93L, 93L, 93L, 94L, 94L, 94L, 94L), score = c(4.7000000000000002, 4.0999999999999996, 3.8999999999999999, 4.7999999999999998, 4.5999999999999996, 4.2999999999999998, 2.7999999999999998, 4.0999999999999996, 3.3999999999999999, 4.5, 3.7999999999999998, 4.5, 4.5999999999999996, 3.8999999999999999, 3.8999999999999999, 4.2999999999999998, 4.5, 4.7999999999999998, 4.5999999999999996, 4.5999999999999996, 4.9000000000000004, 4.5999999999999996, 4.5, 4.4000000000000004, 4.5999999999999996, 4.7000000000000002, 4.5, 4.7999999999999998, 4.9000000000000004, 4.5, 4.4000000000000004, 4.2999999999999998, 4.0999999999999996, 4.2000000000000002, 3.5, 3.3999999999999999, 4.5, 4.4000000000000004, 4.4000000000000004, 2.5, 4.2999999999999998, 4.5, 4.7999999999999998, 4.7999999999999998, 4.4000000000000004, 4.7000000000000002, 4.4000000000000004, 4.7000000000000002, 4.5, 4, 4.2999999999999998, 4.4000000000000004, 4.5, 5, 4.9000000000000004, 4.5999999999999996, 5, 4.7000000000000002, 5, 3.6000000000000001, 3.7000000000000002, 4.2999999999999998, 4.0999999999999996, 4.2000000000000002, 4.7000000000000002, 4.7000000000000002, 3.5, 4.0999999999999996, 4.2000000000000002, 4, 4, 3.8999999999999999, 4.4000000000000004, 3.7999999999999998, 3.5, 4.2000000000000002, 3.5, 3.6000000000000001, 2.8999999999999999, 3.2999999999999998, 3.2999999999999998, 3.2000000000000002, 4.5999999999999996, 4.2000000000000002, 4.2999999999999998, 4.4000000000000004, 4.0999999999999996, 4.5999999999999996, 4.4000000000000004, 4.7999999999999998, 4.2999999999999998, 3.6000000000000001, 4.2999999999999998, 4, 4.2000000000000002, 4.0999999999999996, 4.0999999999999996, 4.4000000000000004, 4.2999999999999998, 4.4000000000000004, 4.4000000000000004, 4.9000000000000004, 5, 4.4000000000000004, 4.7999999999999998, 4.9000000000000004, 4.2999999999999998, 5, 4.7000000000000002, 4.5, 3.5, 3.8999999999999999, 4, 4, 3.7000000000000002, 3.3999999999999999, 3.2999999999999998, 3.7999999999999998, 3.8999999999999999, 3.3999999999999999, 3.7000000000000002, 4.0999999999999996, 3.7000000000000002, 3.5, 3.5, 4.4000000000000004, 3.3999999999999999, 4.2999999999999998, 3.7000000000000002, 4.7000000000000002, 3.8999999999999999, 3.6000000000000001, 4.5, 4.5, 4.7999999999999998, 4.7999999999999998, 4.7000000000000002, 4.5, 4.2999999999999998, 4.7999999999999998, 4.0999999999999996, 4.4000000000000004, 4.2999999999999998, 3.6000000000000001, 4.5, 4.2999999999999998, 4.4000000000000004, 4.7000000000000002, 4.7999999999999998, 3.5, 3.7999999999999998, 3.6000000000000001, 4.2000000000000002, 3.6000000000000001, 4.4000000000000004, 3.7000000000000002, 4.2999999999999998, 4.5999999999999996, 4.5999999999999996, 4.0999999999999996, 3.6000000000000001, 2.2999999999999998, 4.2999999999999998, 4.4000000000000004, 3.6000000000000001, 4.4000000000000004, 3.8999999999999999, 3.7999999999999998, 3.3999999999999999, 4.9000000000000004, 4.0999999999999996, 3.2000000000000002, 4.2000000000000002, 3.8999999999999999, 4.9000000000000004, 4.7000000000000002, 4.4000000000000004, 4.2000000000000002, 4, 4.4000000000000004, 3.8999999999999999, 4.4000000000000004, 3, 3.5, 2.7999999999999998, 4.5999999999999996, 4.2999999999999998, 3.3999999999999999, 3, 4.2000000000000002, 4.2999999999999998, 4.0999999999999996, 4.5999999999999996, 3.8999999999999999, 3.5, 4, 4, 3.8999999999999999, 3.2999999999999998, 4, 3.7999999999999998, 4.2000000000000002, 4, 3.7999999999999998, 3.2999999999999998, 4.0999999999999996, 4.7000000000000002, 4.4000000000000004, 4.7999999999999998, 4.7999999999999998, 4.5999999999999996, 4.5999999999999996, 4.7999999999999998, 4.4000000000000004, 4.7000000000000002, 4.7000000000000002, 3.2999999999999998, 4.4000000000000004, 4.2999999999999998, 4.9000000000000004, 4.4000000000000004, 4.7000000000000002, 4.2999999999999998, 4.7999999999999998, 4.5, 4.7000000000000002, 3.2999999999999998, 4.7000000000000002, 4.5999999999999996, 3.6000000000000001, 4, 4.0999999999999996, 4, 4.5, 4.5999999999999996, 4.7999999999999998, 4.5999999999999996, 4.9000000000000004, 3.1000000000000001, 3.7000000000000002, 3.7000000000000002, 3.8999999999999999, 3.8999999999999999, 3.2000000000000002, 4.4000000000000004, 4.2000000000000002, 4.7000000000000002, 3.8999999999999999, 3.6000000000000001, 3.3999999999999999, 4.4000000000000004, 4.4000000000000004, 4.0999999999999996, 3.6000000000000001, 3.5, 4.0999999999999996, 3.7999999999999998, 4, 4.7999999999999998, 4.2000000000000002, 4.5999999999999996, 4.2999999999999998, 4.7999999999999998, 3.7999999999999998, 4.5, 4.9000000000000004, 4.9000000000000004, 4.7999999999999998, 4.7000000000000002, 4.5999999999999996, 4.2999999999999998, 4.4000000000000004, 4.5, 4.2000000000000002, 4.7999999999999998, 4.5999999999999996, 4.9000000000000004, 4.7999999999999998, 4.7999999999999998, 4.5999999999999996, 4.7000000000000002, 4.0999999999999996, 3.7999999999999998, 4, 4.0999999999999996, 4, 4.0999999999999996, 3.5, 4.0999999999999996, 3.6000000000000001, 4, 3.8999999999999999, 3.7999999999999998, 4.4000000000000004, 4.7000000000000002, 3.7999999999999998, 4.0999999999999996, 4.0999999999999996, 4.7000000000000002, 4.2999999999999998, 4.4000000000000004, 4.5, 3.1000000000000001, 3.7000000000000002, 4.5, 3, 4.5999999999999996, 3.7000000000000002, 3.6000000000000001, 3.2000000000000002, 3.2999999999999998, 2.8999999999999999, 4.2000000000000002, 4.5, 3.7999999999999998, 3.7000000000000002, 3.7000000000000002, 4, 3.7000000000000002, 4.5, 3.7999999999999998, 3.8999999999999999, 4.5999999999999996, 4.5, 4.2000000000000002, 4, 3.7999999999999998, 3.5, 2.7000000000000002, 4, 4.5999999999999996, 3.8999999999999999, 4.5, 3.7000000000000002, 2.3999999999999999, 3.1000000000000001, 2.5, 3, 4.5, 4.7999999999999998, 4.9000000000000004, 4.5, 4.5999999999999996, 4.5, 4.9000000000000004, 4.4000000000000004, 4.5999999999999996, 4.5999999999999996, 5, 4.9000000000000004, 4.5999999999999996, 4.7999999999999998, 4.9000000000000004, 4.9000000000000004, 4.9000000000000004, 5, 4.5, 3.5, 3.7999999999999998, 3.8999999999999999, 3.8999999999999999, 4.2000000000000002, 4.0999999999999996, 4.7999999999999998, 4.7999999999999998, 4.7999999999999998, 4.7999999999999998, 4.9000000000000004, 4.2000000000000002, 4.5, 3.8999999999999999, 4.4000000000000004, 4, 3.6000000000000001, 3.7000000000000002, 2.7000000000000002, 4.5, 4.4000000000000004, 3.8999999999999999, 3.6000000000000001, 4.4000000000000004, 4.4000000000000004, 4.7000000000000002, 4.5, 4.0999999999999996, 3.7000000000000002, 4.2999999999999998, 3.5, 3.7000000000000002, 4, 4, 3.1000000000000001, 4.5, 4.7999999999999998, 4.2000000000000002, 4.9000000000000004, 4.7999999999999998, 3.5, 3.6000000000000001, 4.4000000000000004, 3.3999999999999999, 3.8999999999999999, 3.7999999999999998, 4.7999999999999998, 4.5999999999999996, 5, 3.7999999999999998, 4.2000000000000002, 3.2999999999999998, 4.7000000000000002, 4.5999999999999996, 4.5999999999999996, 4, 4.2000000000000002, 4.9000000000000004, 4.5, 4.7999999999999998, 3.7999999999999998, 4.7999999999999998, 5, 5, 4.9000000000000004, 4.5999999999999996, 5, 4.7999999999999998, 4.9000000000000004, 4.9000000000000004, 3.8999999999999999, 3.8999999999999999, 4.5, 4.5, 3.2999999999999998, 3.1000000000000001, 2.7999999999999998, 3.1000000000000001, 4.2000000000000002, 3.3999999999999999, 3, 3.2999999999999998, 3.6000000000000001, 3.7000000000000002, 3.6000000000000001, 4.2999999999999998, 4.0999999999999996, 4.9000000000000004, 4.7999999999999998, 3.7000000000000002, 3.8999999999999999, 4.5, 3.6000000000000001, 4.4000000000000004, 3.3999999999999999, 4.4000000000000004, 4.5, 4.5, 4.5, 4.5999999999999996, 4.0999999999999996, 4.5, 3.5, 4.4000000000000004, 4.4000000000000004, 4.0999999999999996 ), rank = structure(c(2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("teaching", "tenure track", "tenured" ), class = "factor"), ethnicity = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L), .Label = c("minority", "not minority"), class = "factor"), gender = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L), .Label = c("female", "male"), class = "factor"), language = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), .Label = c("english", "non-english"), class = "factor"), age = c(36L, 36L, 36L, 36L, 59L, 59L, 59L, 51L, 51L, 40L, 40L, 40L, 40L, 40L, 40L, 40L, 40L, 31L, 31L, 31L, 31L, 31L, 31L, 62L, 62L, 62L, 62L, 62L, 62L, 62L, 33L, 33L, 33L, 33L, 33L, 51L, 51L, 51L, 51L, 51L, 51L, 51L, 33L, 33L, 33L, 33L, 33L, 33L, 33L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 35L, 35L, 35L, 37L, 37L, 37L, 37L, 37L, 42L, 42L, 42L, 42L, 42L, 42L, 42L, 49L, 49L, 49L, 49L, 37L, 37L, 37L, 37L, 45L, 45L, 45L, 45L, 45L, 45L, 56L, 56L, 56L, 56L, 56L, 48L, 48L, 48L, 48L, 48L, 48L, 48L, 48L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 46L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 52L, 52L, 52L, 52L, 52L, 52L, 29L, 62L, 62L, 62L, 62L, 62L, 64L, 64L, 64L, 64L, 64L, 64L, 64L, 34L, 34L, 58L, 58L, 58L, 58L, 58L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 73L, 73L, 73L, 73L, 70L, 70L, 70L, 70L, 41L, 63L, 63L, 63L, 63L, 63L, 63L, 63L, 47L, 47L, 47L, 39L, 39L, 39L, 39L, 39L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 54L, 54L, 54L, 44L, 44L, 44L, 44L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 62L, 62L, 62L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 37L, 42L, 42L, 42L, 42L, 42L, 35L, 35L, 35L, 35L, 39L, 39L, 39L, 39L, 49L, 49L, 49L, 61L, 61L, 61L, 61L, 33L, 33L, 33L, 58L, 56L, 56L, 56L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 33L, 33L, 33L, 33L, 33L, 33L, 57L, 57L, 57L, 57L, 38L, 38L, 38L, 38L, 38L, 38L, 38L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 34L, 32L, 32L, 32L, 32L, 32L, 42L, 42L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 35L, 35L, 62L, 62L, 62L, 42L, 39L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 64L, 64L, 64L, 64L, 64L, 64L, 50L, 50L, 60L, 60L, 60L, 51L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 52L, 52L, 52L, 52L, 52L, 52L, 51L, 51L, 51L, 51L, 51L, 38L, 38L, 38L, 38L, 47L, 47L, 43L, 43L, 38L, 38L, 38L, 38L, 38L, 38L, 43L, 43L, 43L, 43L, 57L, 57L, 57L, 51L, 51L, 51L, 51L, 45L, 45L, 45L, 45L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 57L, 47L, 47L, 47L, 47L, 47L, 54L, 54L, 54L, 54L, 54L, 58L, 58L, 58L, 58L, 58L, 58L, 58L, 58L, 42L, 42L, 42L, 33L, 33L, 62L, 62L, 62L, 62L, 62L, 62L, 62L, 35L, 35L, 35L, 61L, 61L, 52L, 52L, 52L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 32L, 32L, 32L, 32L, 32L, 32L, 42L, 42L, 42L, 42L), cls_perc_eval = c(55.813949999999998, 68.799999999999997, 60.799999999999997, 62.60163, 85, 87.5, 88.636359999999996, 100, 56.923079999999999, 86.956519999999998, 88.888890000000004, 96, 85, 56, 88.095240000000004, 90, 83.333340000000007, 87.5, 90.909090000000006, 79.166659999999993, 88.888890000000004, 88.135589999999993, 56.321840000000002, 64.539010000000005, 54.794519999999999, 60.76923, 61.754390000000001, 56.985289999999999, 58.041960000000003, 61.589410000000001, 80.487809999999996, 85.294120000000007, 90.243899999999996, 70.731700000000004, 82.352940000000004, 60.975610000000003, 95.454539999999994, 61.904760000000003, 94.117649999999998, 80, 100, 100, 80, 87.878780000000006, 25, 59.183669999999999, 86.206890000000001, 87.5, 85, 84.210530000000006, 75, 93.333340000000007, 95.652180000000001, 90.909090000000006, 58.620690000000003, 76.190479999999994, 83.333340000000007, 84.210530000000006, 80, 72, 90.909090000000006, 95.833340000000007, 88.235290000000006, 61.904760000000003, 80, 96, 71.428569999999993, 70, 60, 66.666659999999993, 43.859650000000002, 70.175439999999995, 78.431370000000001, 60, 83.333340000000007, 83.783779999999993, 51.724139999999998, 85.185190000000006, 82.142859999999999, 65.384609999999995, 80.769229999999993, 96.666659999999993, 69.696969999999993, 25.423729999999999, 45.226129999999998, 84.375, 94.5946, 74.53416, 65.853660000000005, 88.636359999999996, 66.037729999999996, 69.38776, 84.375, 74.074070000000006, 60.606059999999999, 73.684209999999993, 58.55856, 63.758389999999999, 66.666659999999993, 62.5, 80.714290000000005, 80.645160000000004, 93.333340000000007, 79.31035, 92, 50, 66.666659999999993, 100, 81.578950000000006, 80, 60.714289999999998, 43.478259999999999, 78.947360000000003, 30.43478, 31.818180000000002, 70, 42.105260000000001, 73.913039999999995, 45.454540000000001, 80, 86.363640000000004, 87.096770000000006, 95.238100000000003, 86.111109999999996, 89.473690000000005, 62.16216, 73.076920000000001, 76.923079999999999, 51.086959999999998, 92, 50.955410000000001, 37.195120000000003, 62.5, 75, 46.808509999999998, 71.428569999999993, 73.333340000000007, 62.5, 53.846150000000002, 76.923079999999999, 82.5, 52.830190000000002, 47.019869999999997, 76.595740000000006, 59.836069999999999, 68.888890000000004, 81.25, 100, 75, 83.333340000000007, 68.75, 80, 64.285709999999995, 70.588229999999996, 76.923079999999999, 76.190479999999994, 76.470590000000001, 35.074629999999999, 10.41667, 53.125, 34.782609999999998, 83.333340000000007, 65.116280000000003, 78.571430000000007, 66.666659999999993, 77.777780000000007, 75, 80, 48.936169999999997, 66.666659999999993, 71.428569999999993, 83.333340000000007, 34.959350000000001, 48.734180000000002, 80, 93.333340000000007, 93.103449999999995, 100, 100, 100, 92.307689999999994, 70, 96.153850000000006, 92.307689999999994, 92.307689999999994, 95.238100000000003, 100, 92.592590000000001, 96.296300000000002, 96, 100, 66.666659999999993, 94.117649999999998, 54.545459999999999, 72.916659999999993, 100, 89.743589999999998, 74.074070000000006, 64.285709999999995, 80.769229999999993, 81.25, 81.25, 92.307689999999994, 100, 88.235290000000006, 92.307689999999994, 86.666659999999993, 70, 73.529409999999999, 75, 78.571430000000007, 66.666659999999993, 61.538460000000001, 42.857140000000001, 68.888890000000004, 80, 88.235290000000006, 92.857140000000001, 100, 92.857140000000001, 100, 86.666659999999993, 82.352940000000004, 91.304339999999996, 85.964910000000003, 88, 91.666659999999993, 78.260869999999997, 86.956519999999998, 96.428569999999993, 62.22222, 64.285709999999995, 85.964910000000003, 81.481480000000005, 81.578950000000006, 86.363640000000004, 62.790700000000001, 96.774190000000004, 92.307689999999994, 86.666659999999993, 76.470590000000001, 63.157890000000002, 80, 73.913039999999995, 81.481480000000005, 75, 66.666659999999993, 95.833340000000007, 90.476190000000003, 64.285709999999995, 79.31035, 85.074619999999996, 91.011240000000001, 90.243899999999996, 83.606560000000002, 71.755719999999997, 78.070179999999993, 89.261740000000003, 95.652180000000001, 79.591840000000005, 81.481480000000005, 90, 90, 86.956519999999998, 66.666659999999993, 100, 90.909090000000006, 71.428569999999993, 63.636360000000003, 100, 89.610389999999995, 87.804879999999997, 81.818179999999998, 80.769229999999993, 70.769229999999993, 69.426749999999998, 79.411770000000004, 76.119399999999999, 76.25, 74.452550000000002, 84.057969999999997, 59.34066, 57.5, 58.888890000000004, 55.882350000000002, 56.164380000000001, 56.818179999999998, 66.666659999999993, 80, 57.142859999999999, 34.274189999999997, 41.071429999999999, 39.676110000000001, 90.909090000000006, 69.902919999999995, 70.967740000000006, 62.195120000000003, 68.627449999999996, 51.428570000000001, 76.470590000000001, 75.675669999999997, 92.857140000000001, 65.413539999999998, 67.322839999999999, 76.923079999999999, 58.865250000000003, 100, 57.894739999999999, 52.380949999999999, 81.481480000000005, 56.25, 73.684209999999993, 52.325580000000002, 75.862070000000003, 72.727270000000004, 71.428569999999993, 70.454539999999994, 75.384609999999995, 50.79365, 78.666659999999993, 81.395349999999993, 73.75, 86.538460000000001, 70.833340000000007, 75.757580000000004, 67, 81.818179999999998, 50, 81.818179999999998, 45.454540000000001, 50, 100, 93.75, 90, 71.875, 70, 62.5, 70.149249999999995, 86.363640000000004, 53.571429999999999, 60, 73.333340000000007, 76.923079999999999, 94.44444, 84.615390000000005, 60, 100, 70.833340000000007, 90.909090000000006, 84, 88.461539999999999, 86.363640000000004, 76.923079999999999, 85, 81.818179999999998, 95.238100000000003, 90.476190000000003, 66.666659999999993, 70.769229999999993, 62.903219999999997, 50.746270000000003, 72.5, 60, 60.627180000000003, 64.248699999999999, 63.873370000000001, 65.404470000000003, 61.100569999999998, 50.574710000000003, 78.571430000000007, 50.632910000000003, 65.217389999999995, 79.166659999999993, 56.716419999999999, 45.631070000000001, 48.947369999999999, 48.529409999999999, 60, 45.3125, 74.193550000000002, 58.064520000000002, 81.08108, 76.923079999999999, 61.538460000000001, 80, 82.278480000000002, 53.846150000000002, 54.081629999999997, 59.793819999999997, 81.818179999999998, 85.897440000000003, 64.285709999999995, 85, 70.588229999999996, 85, 68.421049999999994, 73.076920000000001, 92.857140000000001, 66.666659999999993, 100, 84.210530000000006, 75, 87.5, 91.666659999999993, 88.235290000000006, 40, 93.75, 70.588229999999996, 76.190479999999994, 88.235290000000006, 100, 94.117649999999998, 88.235290000000006, 100, 93.75, 80.769229999999993, 77.777780000000007, 80, 94.117649999999998, 100, 85.714290000000005, 85, 95, 84.615390000000005, 87.5, 94.117649999999998, 83.333340000000007, 91.666659999999993, 85, 70.833340000000007, 43.225810000000003, 28.947369999999999, 40, 40.939599999999999, 35.766419999999997, 44.827590000000001, 50.909089999999999, 49.264710000000001, 62.5, 33.333329999999997, 39.814819999999997, 69.230770000000007, 86.666659999999993, 54.95496, 82.352940000000004, 100, 85.185190000000006, 94.736840000000001, 84.615390000000005, 94.736840000000001, 50, 35, 88.888890000000004, 74.242419999999996, 87.401570000000007, 72.941180000000003, 75.247529999999998, 42.857140000000001, 60.465110000000003, 57.142859999999999, 77.611940000000004, 81.818179999999998, 80 ), cls_did_eval = c(24L, 86L, 76L, 77L, 17L, 35L, 39L, 55L, 111L, 40L, 24L, 24L, 17L, 14L, 37L, 18L, 15L, 42L, 40L, 38L, 40L, 52L, 49L, 182L, 160L, 79L, 176L, 155L, 166L, 186L, 33L, 29L, 37L, 29L, 28L, 25L, 21L, 13L, 16L, 24L, 23L, 20L, 48L, 29L, 11L, 29L, 25L, 42L, 34L, 16L, 12L, 14L, 22L, 10L, 17L, 16L, 15L, 16L, 16L, 18L, 30L, 23L, 30L, 13L, 24L, 24L, 25L, 28L, 18L, 28L, 25L, 40L, 40L, 18L, 30L, 31L, 15L, 23L, 23L, 34L, 21L, 29L, 23L, 45L, 90L, 27L, 35L, 120L, 27L, 39L, 35L, 34L, 27L, 100L, 20L, 14L, 65L, 95L, 18L, 85L, 113L, 25L, 14L, 23L, 23L, 9L, 30L, 15L, 31L, 12L, 17L, 10L, 15L, 7L, 7L, 14L, 8L, 17L, 10L, 12L, 19L, 27L, 20L, 31L, 17L, 23L, 19L, 30L, 94L, 46L, 80L, 61L, 15L, 51L, 22L, 10L, 11L, 15L, 21L, 20L, 33L, 84L, 71L, 36L, 73L, 31L, 13L, 23L, 12L, 15L, 11L, 12L, 18L, 12L, 10L, 16L, 13L, 47L, 5L, 34L, 24L, 10L, 28L, 11L, 10L, 14L, 12L, 8L, 23L, 10L, 10L, 10L, 86L, 154L, 12L, 14L, 27L, 21L, 8L, 16L, 24L, 7L, 25L, 24L, 24L, 20L, 12L, 25L, 26L, 24L, 15L, 10L, 16L, 30L, 35L, 21L, 35L, 20L, 9L, 21L, 13L, 13L, 12L, 14L, 15L, 12L, 13L, 7L, 25L, 12L, 11L, 8L, 24L, 15L, 31L, 36L, 15L, 13L, 14L, 13L, 12L, 13L, 42L, 21L, 49L, 44L, 22L, 18L, 20L, 27L, 28L, 27L, 49L, 22L, 31L, 19L, 27L, 30L, 12L, 13L, 26L, 12L, 16L, 17L, 22L, 24L, 14L, 23L, 19L, 18L, 23L, 57L, 81L, 74L, 102L, 94L, 89L, 133L, 22L, 78L, 22L, 27L, 27L, 60L, 10L, 10L, 10L, 10L, 7L, 14L, 69L, 36L, 72L, 63L, 46L, 109L, 54L, 51L, 61L, 102L, 58L, 54L, 46L, 53L, 19L, 41L, 25L, 24L, 16L, 20L, 85L, 69L, 98L, 20L, 72L, 44L, 51L, 35L, 18L, 26L, 28L, 13L, 174L, 171L, 10L, 166L, 17L, 11L, 22L, 22L, 9L, 14L, 45L, 22L, 64L, 70L, 31L, 49L, 32L, 59L, 35L, 59L, 45L, 34L, 50L, 67L, 9L, 8L, 18L, 5L, 5L, 16L, 15L, 9L, 23L, 7L, 10L, 47L, 19L, 15L, 18L, 11L, 10L, 17L, 22L, 18L, 14L, 17L, 20L, 21L, 23L, 19L, 20L, 17L, 18L, 20L, 19L, 46L, 46L, 39L, 34L, 29L, 27L, 348L, 372L, 343L, 380L, 322L, 44L, 66L, 40L, 60L, 19L, 38L, 47L, 93L, 33L, 36L, 29L, 23L, 36L, 30L, 10L, 8L, 12L, 65L, 7L, 53L, 58L, 9L, 67L, 36L, 17L, 12L, 17L, 13L, 19L, 13L, 12L, 12L, 16L, 12L, 14L, 11L, 15L, 6L, 15L, 12L, 16L, 15L, 10L, 16L, 15L, 18L, 15L, 21L, 14L, 16L, 16L, 21L, 18L, 17L, 19L, 11L, 14L, 16L, 15L, 22L, 17L, 85L, 67L, 11L, 28L, 61L, 49L, 13L, 28L, 67L, 60L, 20L, 43L, 27L, 13L, 61L, 14L, 19L, 23L, 18L, 11L, 18L, 11L, 7L, 24L, 98L, 111L, 62L, 76L, 9L, 52L, 48L, 52L, 54L, 28L), cls_students = c(43L, 125L, 125L, 123L, 20L, 40L, 44L, 55L, 195L, 46L, 27L, 25L, 20L, 25L, 42L, 20L, 18L, 48L, 44L, 48L, 45L, 59L, 87L, 282L, 292L, 130L, 285L, 272L, 286L, 302L, 41L, 34L, 41L, 41L, 34L, 41L, 22L, 21L, 17L, 30L, 23L, 20L, 60L, 33L, 44L, 49L, 29L, 48L, 40L, 19L, 16L, 15L, 23L, 11L, 29L, 21L, 18L, 19L, 20L, 25L, 33L, 24L, 34L, 21L, 30L, 25L, 35L, 40L, 30L, 42L, 57L, 57L, 51L, 30L, 36L, 37L, 29L, 27L, 28L, 52L, 26L, 30L, 33L, 177L, 199L, 32L, 37L, 161L, 41L, 44L, 53L, 49L, 32L, 135L, 33L, 19L, 111L, 149L, 27L, 136L, 140L, 31L, 15L, 29L, 25L, 18L, 45L, 15L, 38L, 15L, 28L, 23L, 19L, 23L, 22L, 20L, 19L, 23L, 22L, 15L, 22L, 31L, 21L, 36L, 19L, 37L, 26L, 39L, 184L, 50L, 157L, 164L, 24L, 68L, 47L, 14L, 15L, 24L, 39L, 26L, 40L, 159L, 151L, 47L, 122L, 45L, 16L, 23L, 16L, 18L, 16L, 15L, 28L, 17L, 13L, 21L, 17L, 134L, 48L, 64L, 69L, 12L, 43L, 14L, 15L, 18L, 16L, 10L, 47L, 15L, 14L, 12L, 246L, 316L, 15L, 15L, 29L, 21L, 8L, 16L, 26L, 10L, 26L, 26L, 26L, 21L, 12L, 27L, 27L, 25L, 15L, 15L, 17L, 55L, 48L, 21L, 39L, 27L, 14L, 26L, 16L, 16L, 13L, 14L, 17L, 13L, 15L, 10L, 34L, 16L, 14L, 12L, 39L, 35L, 45L, 45L, 17L, 14L, 14L, 14L, 12L, 15L, 51L, 23L, 57L, 50L, 24L, 23L, 23L, 28L, 45L, 42L, 57L, 27L, 38L, 22L, 43L, 31L, 13L, 15L, 34L, 19L, 20L, 23L, 27L, 32L, 21L, 24L, 21L, 28L, 29L, 67L, 89L, 82L, 122L, 131L, 114L, 149L, 23L, 98L, 27L, 30L, 30L, 69L, 15L, 10L, 11L, 14L, 11L, 14L, 77L, 41L, 88L, 78L, 65L, 157L, 68L, 67L, 80L, 137L, 69L, 91L, 80L, 90L, 34L, 73L, 44L, 36L, 20L, 35L, 248L, 168L, 247L, 22L, 103L, 62L, 82L, 51L, 35L, 34L, 37L, 14L, 266L, 254L, 13L, 282L, 17L, 19L, 42L, 27L, 16L, 19L, 86L, 29L, 88L, 98L, 44L, 65L, 63L, 75L, 43L, 80L, 52L, 48L, 66L, 100L, 11L, 16L, 22L, 11L, 10L, 16L, 16L, 10L, 32L, 10L, 16L, 67L, 22L, 28L, 30L, 15L, 13L, 18L, 26L, 30L, 14L, 24L, 22L, 25L, 26L, 22L, 26L, 20L, 22L, 21L, 21L, 69L, 65L, 62L, 67L, 40L, 45L, 574L, 579L, 537L, 581L, 527L, 87L, 84L, 79L, 92L, 24L, 67L, 103L, 190L, 68L, 60L, 64L, 31L, 62L, 37L, 13L, 13L, 15L, 79L, 13L, 98L, 97L, 11L, 78L, 56L, 20L, 17L, 20L, 19L, 26L, 14L, 18L, 12L, 19L, 16L, 16L, 12L, 17L, 15L, 16L, 17L, 21L, 17L, 10L, 17L, 17L, 18L, 16L, 26L, 18L, 20L, 17L, 21L, 21L, 20L, 20L, 13L, 16L, 17L, 18L, 24L, 20L, 120L, 155L, 38L, 70L, 149L, 137L, 29L, 55L, 136L, 96L, 60L, 108L, 39L, 15L, 111L, 17L, 19L, 27L, 19L, 13L, 19L, 22L, 20L, 27L, 132L, 127L, 85L, 101L, 21L, 86L, 84L, 67L, 66L, 35L), cls_level = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L), .Label = c("lower", "upper"), class = "factor"), cls_profs = structure(c(2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("multiple", "single"), class = "factor"), cls_credits = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L), .Label = c("multi credit", "one credit"), class = "factor"), bty_f1lower = c(5L, 5L, 5L, 5L, 4L, 4L, 4L, 5L, 5L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 7L, 7L, 7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 3L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 8L, 8L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 8L, 8L, 8L, 8L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 1L, 1L, 1L, 3L, 5L, 5L, 5L, 6L, 6L, 6L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 1L, 1L, 1L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 7L, 7L, 7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 7L, 7L, 7L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 3L, 3L, 3L, 3L), bty_f1upper = c(7L, 7L, 7L, 7L, 4L, 4L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 9L, 9L, 9L, 9L, 9L, 9L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 3L, 3L, 3L, 3L, 7L, 7L, 7L, 7L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 9L, 9L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 6L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 8L, 8L, 8L, 8L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 8L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 8L, 8L, 8L, 6L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 7L, 7L, 7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 1L, 1L, 1L, 1L, 1L, 1L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 1L, 8L, 7L, 7L, 7L, 7L, 7L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 7L, 7L, 1L, 1L, 1L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 4L, 4L, 4L, 4L, 7L, 7L, 6L, 6L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 8L, 8L, 8L, 8L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 6L, 6L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 5L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 7L, 7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 9L, 9L, 9L, 2L, 2L, 8L, 8L, 8L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L), bty_f2upper = c(6L, 6L, 6L, 6L, 2L, 2L, 2L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 9L, 9L, 9L, 9L, 9L, 9L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 2L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 3L, 3L, 3L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 8L, 8L, 8L, 8L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 8L, 8L, 8L, 8L, 7L, 7L, 7L, 4L, 4L, 4L, 4L, 7L, 7L, 7L, 7L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 9L, 9L, 9L, 9L, 9L, 9L, 6L, 6L, 6L, 6L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 4L, 4L, 4L, 4L, 4L, 4L, 7L, 7L, 7L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 5L, 5L, 5L, 6L, 6L, 7L, 7L, 9L, 9L, 9L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 9L, 9L, 2L, 2L, 2L, 7L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 4L, 4L, 4L, 4L, 6L, 6L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 10L, 10L, 10L, 7L, 7L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 9L, 9L, 9L, 9L, 9L, 9L, 7L, 7L, 7L, 7L ), bty_m1lower = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 7L, 7L, 7L, 7L, 7L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 6L, 6L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 6L, 6L, 6L, 6L, 6L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 3L, 3L, 3L, 3L, 3L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 2L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 6L, 6L, 6L, 3L, 3L, 3L, 3L, 3L, 6L, 6L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 1L, 1L, 1L, 1L, 4L, 3L, 3L, 5L, 5L, 5L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 2L, 2L, 2L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 2L, 3L, 3L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 6L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 7L, 7L, 7L, 7L, 7L, 7L, 4L, 4L, 4L, 4L), bty_m1upper = c(4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 7L, 7L, 7L, 7L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 7L, 7L, 7L, 7L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 8L, 8L, 8L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 1L, 5L, 8L, 8L, 6L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 8L, 8L, 2L, 2L, 2L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 3L, 3L, 3L, 3L, 6L, 6L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 8L, 8L, 8L, 8L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 7L, 7L, 7L, 3L, 3L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 6L, 6L, 6L, 6L), bty_m2upper = c(6L, 6L, 6L, 6L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 7L, 7L, 7L, 7L, 7L, 7L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 2L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 8L, 8L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 2L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 8L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 9L, 9L, 9L, 9L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 7L, 7L, 7L, 7L, 7L, 7L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 6L, 6L, 6L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 7L, 7L, 2L, 2L, 2L, 6L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 8L, 8L, 8L, 4L, 4L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L), bty_avg = c(5, 5, 5, 5, 3, 3, 3, 3.3330000000000002, 3.3330000000000002, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 7.3330000000000002, 7.3330000000000002, 7.3330000000000002, 7.3330000000000002, 7.3330000000000002, 7.3330000000000002, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4, 4, 4, 4, 4, 4, 4, 4.6669999999999998, 4.6669999999999998, 4.6669999999999998, 4.6669999999999998, 4.6669999999999998, 4.6669999999999998, 4.6669999999999998, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4, 4, 4, 4, 5.5, 5.5, 5.5, 5.5, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 2.5, 2.5, 2.5, 2.5, 2.5, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 2.8330000000000002, 3, 3, 3, 3, 3, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 4.1669999999999998, 7.8330000000000002, 7.8330000000000002, 3.8330000000000002, 3.8330000000000002, 3.8330000000000002, 3.8330000000000002, 3.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 3, 3, 3, 3, 3, 3, 3, 3, 5.1669999999999998, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 2.6669999999999998, 2.6669999999999998, 2.6669999999999998, 5.5, 5.5, 5.5, 5.5, 5.5, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 6.5, 6.5, 6.5, 6.5, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 3, 3, 3, 3.6669999999999998, 3.6669999999999998, 3.6669999999999998, 3.6669999999999998, 3.6669999999999998, 3.6669999999999998, 3.6669999999999998, 3.6669999999999998, 6.1669999999999998, 4, 4, 4, 4, 4, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 8.1669999999999998, 8.1669999999999998, 8.1669999999999998, 8.1669999999999998, 6.5, 6.5, 6.5, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 4.8330000000000002, 7, 7, 7, 4.6669999999999998, 3.8330000000000002, 3.8330000000000002, 3.8330000000000002, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 3.1669999999999998, 5.8330000000000002, 5.8330000000000002, 5.8330000000000002, 5.8330000000000002, 5.8330000000000002, 5.8330000000000002, 5.6669999999999998, 5.6669999999999998, 5.6669999999999998, 5.6669999999999998, 6.5, 6.5, 6.5, 6.5, 6.5, 6.5, 6.5, 1.667, 1.667, 1.667, 1.667, 1.667, 1.667, 6.6669999999999998, 6.6669999999999998, 6.6669999999999998, 3.6669999999999998, 3.6669999999999998, 3.6669999999999998, 3.8330000000000002, 3.8330000000000002, 6.1669999999999998, 6.1669999999999998, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.6669999999999998, 3.6669999999999998, 3.5, 3.5, 3.5, 2.6669999999999998, 5.6669999999999998, 6, 6, 6.5, 6.5, 6.5, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 2.3330000000000002, 7.1669999999999998, 7.1669999999999998, 1.667, 1.667, 1.667, 5.1669999999999998, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 5.8330000000000002, 5.8330000000000002, 5.8330000000000002, 5.8330000000000002, 5.8330000000000002, 5.8330000000000002, 6.1669999999999998, 6.1669999999999998, 6.1669999999999998, 6.1669999999999998, 6.1669999999999998, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 5.1669999999999998, 5.1669999999999998, 4.1669999999999998, 4.1669999999999998, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 3, 3, 3, 6.3330000000000002, 6.3330000000000002, 6.3330000000000002, 6.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 3.3330000000000002, 2.8330000000000002, 2.8330000000000002, 2.8330000000000002, 2.8330000000000002, 2.8330000000000002, 2.8330000000000002, 2.8330000000000002, 2.8330000000000002, 2.8330000000000002, 2.8330000000000002, 2.8330000000000002, 6.6669999999999998, 6.6669999999999998, 6.6669999999999998, 6.6669999999999998, 6.6669999999999998, 6.8330000000000002, 6.8330000000000002, 6.8330000000000002, 6.8330000000000002, 6.8330000000000002, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 5.8330000000000002, 5.8330000000000002, 2, 2, 2, 2, 2, 2, 2, 7.8330000000000002, 7.8330000000000002, 7.8330000000000002, 3.3330000000000002, 3.3330000000000002, 4.5, 4.5, 4.5, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 4.3330000000000002, 6.8330000000000002, 6.8330000000000002, 6.8330000000000002, 6.8330000000000002, 6.8330000000000002, 6.8330000000000002, 5.3330000000000002, 5.3330000000000002, 5.3330000000000002, 5.3330000000000002), pic_outfit = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("formal", "not formal"), class = "factor"), pic_color = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 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2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("black&white", "color"), class = "factor")), row.names = c(NA, -463L), class = c("tbl_df", "tbl", "data.frame"))