Loading...
Some people have questioned the judge's objectivity in cases of sex discrimination against women. But the record shows that in sixty percent of such cases, the judge has decided in favor of the women. This record demonstrates that the judge has not discriminated against women in cases of sex discrimination against women.
The argument above is flawed in that it ignores the possibility that
| Text from Passage | Analysis |
| Some people have questioned the judge's objectivity in cases of sex discrimination against women. |
|
| But the record shows that in sixty percent of such cases, the judge has decided in favor of the women. |
|
| This record demonstrates that the judge has not discriminated against women in cases of sex discrimination against women. |
|
The argument starts by acknowledging criticism of the judge's objectivity, then presents a statistic showing the judge rules for women 60% of the time, and concludes this proves the judge isn't biased against women.
The judge has not discriminated against women in sex discrimination cases.
The argument assumes that ruling for women 60% of the time automatically proves no bias exists. However, this ignores several key possibilities: we don't know what percentage SHOULD be if the judge were truly objective (maybe it should be 80% or 90% based on case merits), we don't know the strength of the cases, and we don't know how the judge's decisions compare to other judges or legal standards.
Misc. - This is a flaw question asking what possibility the argument ignores. We need to identify what the author overlooked when concluding that a 60% win rate proves no discrimination.
The argument makes a quantitative claim (60% of cases decided in favor of women) and uses this to make a qualitative judgment (no discrimination exists). The precision issue is that the author treats this percentage as definitive proof without considering what other factors might explain this statistic.
For this flaw question, we need to think about what the argument assumes but doesn't explicitly state. The author sees 60% and concludes 'no discrimination' - but what possibilities does this ignore? We should look for scenarios where 60% could still indicate bias, or where this statistic doesn't actually prove objectivity. The key is finding what the author failed to consider when interpreting this data.
This choice suggests the argument ignores that many of the judge's cases involved sex discrimination against women. However, this doesn't identify a flaw in the reasoning. Whether the judge handled many or few such cases doesn't affect the logic that connects a \(\mathrm{60\%}\) win rate to proving no discrimination. The argument's flaw isn't about the volume of cases.
This points to other judges having difficulty being objective in sex discrimination cases. But the argument isn't making any comparison to other judges or claiming this judge is unique. The flaw we're looking for should directly challenge the connection between the \(\mathrm{60\%}\) statistic and the conclusion about this specific judge's objectivity.
This suggests the argument ignores possible bias in non-sex discrimination cases. While this might be true, it's irrelevant to the argument's scope. The argument specifically addresses objectivity 'in cases of sex discrimination against women' and draws conclusions only about those cases. Bias in other types of cases doesn't affect this particular reasoning.
This focuses on whether cases were appealed from lower courts. However, the source of the cases doesn't impact the argument's core logic. Whether cases came from appeals or originated in this court doesn't change the flawed assumption that a \(\mathrm{60\%}\) win rate automatically proves objectivity.
This directly hits the argument's central flaw. The argument treats \(\mathrm{60\%}\) as proof of no discrimination, but this ignores a crucial possibility - what if the evidence in these cases was so strong that women should have won \(\mathrm{80\%}\), \(\mathrm{90\%}\), or even higher percentage of the time? If women deserved to win more than \(\mathrm{60\%}\) based on case merits, then the actual \(\mathrm{60\%}\) rate could indicate bias against women, not objectivity. This choice identifies exactly what the argument overlooks: the need to compare actual outcomes to what the outcomes should be based on evidence quality.