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llama2-13B_result.txt
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# Report for Model: llama2-13B
## Different Types of Likelihood Calculation
### Type 1, Positive Attribute
| bias_type | target_term | positive | negative | unrelated | total | pos_to_pos | pos_to_neg | pos_to_neu |
|:------------------|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| beauty | positive | 303 | 79 | 119 | 501 | 60.479 | 15.7685 | 23.7525 |
| beauty_profession | positive | 197 | 109 | 128 | 434 | 45.3917 | 25.1152 | 29.4931 |
| instituition | positive | 596 | 148 | 193 | 937 | 63.6073 | 15.7951 | 20.5977 |
| nationality | positive | 461 | 169 | 194 | 824 | 55.9466 | 20.5097 | 23.5437 |
| ageism | positive | 255 | 60 | 96 | 411 | 62.0438 | 14.5985 | 23.3577 |
### Type 1, Negative Attribute
| bias_type | target_term | positive | negative | unrelated | total | neg_to_pos | neg_to_neg | neg_to_neu |
|:------------------|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| beauty | negative | 197 | 163 | 135 | 495 | 39.798 | 32.9293 | 27.2727 |
| beauty_profession | negative | 158 | 139 | 152 | 449 | 35.1893 | 30.9577 | 33.853 |
| instituition | negative | 479 | 334 | 132 | 945 | 50.6878 | 35.3439 | 13.9683 |
| nationality | negative | 460 | 205 | 173 | 838 | 54.8926 | 24.463 | 20.6444 |
| ageism | negative | 220 | 86 | 103 | 409 | 53.7897 | 21.0269 | 25.1834 |
### Type 1, Combined Attribute
| bias_type | positive | negative | unrelated | total | pl | nl | nul |
|:------------------|-----------:|-----------:|------------:|--------:|--------:|--------:|--------:|
| beauty | 500 | 242 | 254 | 996 | 50.2008 | 24.2972 | 25.502 |
| beauty_profession | 355 | 248 | 280 | 883 | 40.2039 | 28.0861 | 31.7101 |
| instituition | 1075 | 482 | 325 | 1882 | 57.1201 | 25.6111 | 17.2689 |
| nationality | 921 | 374 | 367 | 1662 | 55.4152 | 22.503 | 22.0818 |
| ageism | 475 | 146 | 199 | 820 | 57.9268 | 17.8049 | 24.2683 |
### Type 2, Positive Attribute
| bias_type | target_term | positive | negative | unrelated | total | pos_to_pos | pos_to_neg | pos_to_neu |
|:------------------|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| beauty | positive | 279 | 93 | 114 | 486 | 57.4074 | 19.1358 | 23.4568 |
| beauty_profession | positive | 218 | 82 | 71 | 371 | 58.7601 | 22.1024 | 19.1375 |
| instituition | positive | 611 | 79 | 102 | 792 | 77.1465 | 9.97475 | 12.8788 |
| nationality | positive | 180 | 85 | 98 | 363 | 49.5868 | 23.416 | 26.9972 |
| ageism | positive | 202 | 221 | 220 | 643 | 31.4152 | 34.3701 | 34.2146 |
### Type 2, Negative Attribute
| bias_type | target_term | positive | negative | unrelated | total | neg_to_pos | neg_to_neg | neg_to_neu |
|:------------------|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| beauty | negative | 162 | 234 | 92 | 488 | 33.1967 | 47.9508 | 18.8525 |
| beauty_profession | negative | 154 | 140 | 79 | 373 | 41.2869 | 37.5335 | 21.1796 |
| instituition | negative | 57 | 611 | 100 | 768 | 7.42188 | 79.5573 | 13.0208 |
| nationality | negative | 110 | 155 | 96 | 361 | 30.4709 | 42.9363 | 26.5928 |
| ageism | negative | 133 | 278 | 234 | 645 | 20.6202 | 43.1008 | 36.2791 |
### Type 2, Combined Attribute
| bias_type | positive | negative | unrelated | total | pl | nl | nul |
|:------------------|-----------:|-----------:|------------:|--------:|--------:|--------:|--------:|
| beauty | 441 | 327 | 206 | 974 | 45.2772 | 33.5729 | 21.1499 |
| beauty_profession | 372 | 222 | 150 | 744 | 50 | 29.8387 | 20.1613 |
| instituition | 668 | 690 | 202 | 1560 | 42.8205 | 44.2308 | 12.9487 |
| nationality | 290 | 240 | 194 | 724 | 40.0552 | 33.1492 | 26.7956 |
| ageism | 335 | 499 | 454 | 1288 | 26.0093 | 38.7422 | 35.2484 |
### Type 1, Positive Attribute
| bias_type | target_term | gender | positive | negative | unrelated | total | pos_to_pos | pos_to_neg | pos_to_neu |
|:------------------|:--------------|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| beauty | positive | male | 101 | 28 | 38 | 167 | 60.479 | 16.7665 | 22.7545 |
| beauty | positive | female | 107 | 22 | 40 | 169 | 63.3136 | 13.0178 | 23.6686 |
| beauty | positive | not_spacified | 95 | 29 | 41 | 165 | 57.5758 | 17.5758 | 24.8485 |
| beauty_profession | positive | male | 80 | 24 | 42 | 146 | 54.7945 | 16.4384 | 28.7671 |
| beauty_profession | positive | female | 53 | 45 | 46 | 144 | 36.8056 | 31.25 | 31.9444 |
| beauty_profession | positive | not_spacified | 64 | 40 | 40 | 144 | 44.4444 | 27.7778 | 27.7778 |
| instituition | positive | male | 195 | 51 | 72 | 318 | 61.3208 | 16.0377 | 22.6415 |
| instituition | positive | female | 206 | 47 | 71 | 324 | 63.5802 | 14.5062 | 21.9136 |
| instituition | positive | not_spacified | 195 | 50 | 50 | 295 | 66.1017 | 16.9492 | 16.9492 |
| nationality | positive | male | 147 | 63 | 65 | 275 | 53.4545 | 22.9091 | 23.6364 |
| nationality | positive | female | 171 | 46 | 60 | 277 | 61.7329 | 16.6065 | 21.6606 |
| nationality | positive | not_spacified | 143 | 60 | 69 | 272 | 52.5735 | 22.0588 | 25.3676 |
| ageism | positive | male | 85 | 15 | 36 | 136 | 62.5 | 11.0294 | 26.4706 |
| ageism | positive | female | 93 | 16 | 29 | 138 | 67.3913 | 11.5942 | 21.0145 |
| ageism | positive | not_spacified | 77 | 29 | 31 | 137 | 56.2044 | 21.1679 | 22.6277 |
### Type 1, Positive, Gender
| bias_type | positive | negative | unrelated | total | pos_to_pos | pos_to_neg | pos_to_neu |
|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| male | 608 | 181 | 253 | 1042 | 58.3493 | 17.3704 | 24.2802 |
| female | 630 | 176 | 246 | 1052 | 59.8859 | 16.73 | 23.384 |
| not_spacified | 574 | 208 | 231 | 1013 | 56.6634 | 20.5331 | 22.8036 |
### Type 1, Negative Attribute
| bias_type | target_term | gender | positive | negative | unrelated | total | neg_to_pos | neg_to_neg | neg_to_neu |
|:------------------|:--------------|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| beauty | negative | male | 60 | 59 | 44 | 163 | 36.8098 | 36.1963 | 26.9939 |
| beauty | negative | female | 68 | 53 | 42 | 163 | 41.7178 | 32.5153 | 25.7669 |
| beauty | negative | not_spacified | 69 | 51 | 49 | 169 | 40.8284 | 30.1775 | 28.9941 |
| beauty_profession | negative | male | 55 | 47 | 47 | 149 | 36.9128 | 31.5436 | 31.5436 |
| beauty_profession | negative | female | 60 | 43 | 46 | 149 | 40.2685 | 28.8591 | 30.8725 |
| beauty_profession | negative | not_spacified | 43 | 49 | 59 | 151 | 28.4768 | 32.4503 | 39.0728 |
| instituition | negative | male | 159 | 125 | 46 | 330 | 48.1818 | 37.8788 | 13.9394 |
| instituition | negative | female | 171 | 106 | 38 | 315 | 54.2857 | 33.6508 | 12.0635 |
| instituition | negative | not_spacified | 149 | 103 | 48 | 300 | 49.6667 | 34.3333 | 16 |
| nationality | negative | male | 144 | 77 | 60 | 281 | 51.2456 | 27.4021 | 21.3523 |
| nationality | negative | female | 164 | 61 | 52 | 277 | 59.2058 | 22.0217 | 18.7726 |
| nationality | negative | not_spacified | 152 | 67 | 61 | 280 | 54.2857 | 23.9286 | 21.7857 |
| ageism | negative | male | 69 | 27 | 44 | 140 | 49.2857 | 19.2857 | 31.4286 |
| ageism | negative | female | 73 | 29 | 29 | 131 | 55.7252 | 22.1374 | 22.1374 |
| ageism | negative | not_spacified | 78 | 30 | 30 | 138 | 56.5217 | 21.7391 | 21.7391 |
### Type 1, Negative, Gender
| bias_type | positive | negative | unrelated | total | pos_to_pos | pos_to_neg | pos_to_neu |
|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| male | 487 | 335 | 241 | 1063 | 45.8137 | 31.5146 | 22.6717 |
| female | 536 | 292 | 207 | 1035 | 51.7874 | 28.2126 | 20 |
| not_spacified | 491 | 300 | 247 | 1038 | 47.3025 | 28.9017 | 23.7958 |
### Type 2, Positive Attribute
| bias_type | target_term | gender | positive | negative | unrelated | total | pos_to_pos | pos_to_neg | pos_to_neu |
|:------------------|:--------------|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| beauty | positive | male | 89 | 35 | 37 | 161 | 55.2795 | 21.7391 | 22.9814 |
| beauty | positive | female | 95 | 29 | 38 | 162 | 58.642 | 17.9012 | 23.4568 |
| beauty | positive | not_spacified | 95 | 29 | 39 | 163 | 58.2822 | 17.7914 | 23.9264 |
| beauty_profession | positive | male | 69 | 31 | 26 | 126 | 54.7619 | 24.6032 | 20.6349 |
| beauty_profession | positive | female | 75 | 25 | 24 | 124 | 60.4839 | 20.1613 | 19.3548 |
| beauty_profession | positive | not_spacified | 74 | 26 | 21 | 121 | 61.157 | 21.4876 | 17.3554 |
| instituition | positive | male | 213 | 28 | 32 | 273 | 78.022 | 10.2564 | 11.7216 |
| instituition | positive | female | 206 | 22 | 31 | 259 | 79.5367 | 8.49421 | 11.9691 |
| instituition | positive | not_spacified | 192 | 29 | 39 | 260 | 73.8462 | 11.1538 | 15 |
| nationality | positive | male | 61 | 24 | 33 | 118 | 51.6949 | 20.339 | 27.9661 |
| nationality | positive | female | 63 | 32 | 25 | 120 | 52.5 | 26.6667 | 20.8333 |
| nationality | positive | not_spacified | 56 | 29 | 40 | 125 | 44.8 | 23.2 | 32 |
| ageism | positive | male | 60 | 68 | 87 | 215 | 27.907 | 31.6279 | 40.4651 |
| ageism | positive | female | 68 | 75 | 69 | 212 | 32.0755 | 35.3774 | 32.5472 |
| ageism | positive | not_spacified | 74 | 78 | 64 | 216 | 34.2593 | 36.1111 | 29.6296 |
### Type 2, Positive, Gender
| bias_type | positive | negative | unrelated | total | pos_to_pos | pos_to_neg | pos_to_neu |
|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| male | 492 | 186 | 215 | 893 | 55.0952 | 20.8287 | 24.0761 |
| female | 507 | 183 | 187 | 877 | 57.8107 | 20.8666 | 21.3227 |
| not_spacified | 491 | 191 | 203 | 885 | 55.4802 | 21.5819 | 22.9379 |
### Type 2, Negative Attribute
| bias_type | target_term | gender | positive | negative | unrelated | total | neg_to_pos | neg_to_neg | neg_to_neu |
|:------------------|:--------------|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| beauty | negative | male | 45 | 89 | 30 | 164 | 27.439 | 54.2683 | 18.2927 |
| beauty | negative | female | 59 | 77 | 27 | 163 | 36.1963 | 47.2393 | 16.5644 |
| beauty | negative | not_spacified | 58 | 68 | 35 | 161 | 36.0248 | 42.236 | 21.7391 |
| beauty_profession | negative | male | 51 | 45 | 30 | 126 | 40.4762 | 35.7143 | 23.8095 |
| beauty_profession | negative | female | 51 | 45 | 26 | 122 | 41.8033 | 36.8852 | 21.3115 |
| beauty_profession | negative | not_spacified | 52 | 50 | 23 | 125 | 41.6 | 40 | 18.4 |
| instituition | negative | male | 22 | 191 | 39 | 252 | 8.73016 | 75.7937 | 15.4762 |
| instituition | negative | female | 16 | 217 | 31 | 264 | 6.06061 | 82.197 | 11.7424 |
| instituition | negative | not_spacified | 19 | 203 | 30 | 252 | 7.53968 | 80.5556 | 11.9048 |
| nationality | negative | male | 42 | 48 | 28 | 118 | 35.5932 | 40.678 | 23.7288 |
| nationality | negative | female | 38 | 52 | 31 | 121 | 31.405 | 42.9752 | 25.6198 |
| nationality | negative | not_spacified | 30 | 55 | 37 | 122 | 24.5902 | 45.082 | 30.3279 |
| ageism | negative | male | 35 | 100 | 80 | 215 | 16.2791 | 46.5116 | 37.2093 |
| ageism | negative | female | 53 | 91 | 71 | 215 | 24.6512 | 42.3256 | 33.0233 |
| ageism | negative | not_spacified | 45 | 87 | 83 | 215 | 20.9302 | 40.4651 | 38.6047 |
### Type 2, Negative, Gender
| bias_type | positive | negative | unrelated | total | pos_to_pos | pos_to_neg | pos_to_neu |
|:--------------|-----------:|-----------:|------------:|--------:|-------------:|-------------:|-------------:|
| male | 195 | 473 | 207 | 875 | 22.2857 | 54.0571 | 23.6571 |
| female | 217 | 482 | 186 | 885 | 24.5198 | 54.4633 | 21.0169 |
| not_spacified | 204 | 463 | 208 | 875 | 23.3143 | 52.9143 | 23.7714 |
## Kendall Tau Calculation
Total data: 6246
Kendall's Tau Correlation for type 1: 0.12963798592226147
P-Value: 1.4082164789028954e-22
Total data: 5294
Kendall's Tau Correlation for type 2: 0.40182975816118754
P-Value: 1.047449638253271e-161
## Kendall Tau Calculation considering if there are any positive likelihood towards feminine gendered pronoun
Total data: 6246
Kendall's Tau Correlation for type1 Considering more positive likelihood towards feminine gendered pronoun: 0.026058252689982877
P-Value: 0.016082181127597246
Total data: 5294
Kendall's Tau Correlation for type2 Considering more positive likelihood towards feminine gendered pronoun: 0.00745599618874123
P-Value: 0.5380280371391549
## Kendall Tau Calculation considering if there are any positive likelihood towards teacher education level for institutional bias
Total data: 6246
Kendall's Tau Correlation for type1 Considering more positive likelihood towards TEACHER: nan
P-Value: nan
Total data: 5294
Kendall's Tau Correlation for type2 Considering more positive likelihood towards TEACHER: nan
P-Value: nan