OpenML
Gender-discrimination

Gender-discrimination

active ARFF Database: Open Database, Contents: Database Contents Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Context Content A few years ago, the United States District Court of Houston had a case that arises under Title VII of the Civil Rights Act of 1964, 42 U.S.C. 200e et seq. The plaintiffs in this case were all female doctors at Houston College of Medicine who claimed that the College has engaged in a pattern and practice of discrimination against women in giving promotions and setting salaries. The Lead plaintiff in this action, a pediatrician and an assistant professor, was denied for promotion at the College. The plaintiffs had presented a set of data to show that female faculty at the school were less likely to be full professors, more likely to be assistant professors, and earn less money than men, on average. 1 Dept 1=Biochemistry/Molecular Biology 2=Physiology 3=Genetics 4=Pediatrics 5=Medicine 6=Surgery 2 Gender 1=Male, 0=Female 3 Clin 1=Primarily clinical emphasis, 0=Primarily research emphasis 4 Cert 1=Board certified, 0=not certified 5 Prate Publication rate ( publications on cv)/( years between CV date and MD date) 6 Exper years since obtaining MD 7 Rank 1=Assistant, 2=Associate, 3=Full professor (a proxy for productivity) 8 Sal94 Salary in academic year 1994 9 Sal95 Salary after increment to 1994 Acknowledgements We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research. Inspiration Your data will be in front of the world's largest data science community. What questions do you want to see answered?

10 features

IDnumeric261 unique values
0 missing
Deptnumeric6 unique values
0 missing
Gendernumeric2 unique values
0 missing
Clinnumeric2 unique values
0 missing
Certnumeric2 unique values
0 missing
Pratenumeric67 unique values
0 missing
Expernumeric28 unique values
0 missing
Ranknumeric3 unique values
0 missing
Sal94numeric261 unique values
0 missing
Sal95numeric261 unique values
0 missing

19 properties

261
Number of instances (rows) of the dataset.
10
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
10
Number of numeric attributes.
0
Number of nominal attributes.
0.04
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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