README.md

Women in High Profile Journals

Online supplementary materials for Shen, Y. A., Shoda, Y., & Fine, I. (2018). Too few women authors on research papers in leading journals. Nature, 555(7695), 165-165.

bioRxiv Pre-Print

Impact Factor Data

Thomas Reuters Impact Factor

NIH RO1 Grant Data

NIH RO1 Grant Award Percentages

Script Processing Order

Downloading Data from PubMed

1. PubMed_DownloadData.ipynb

   • Downloads data from PubMed's server and transforms compressed data into csv files.

2. PubMed_ProcessData.ipynb

   • Extracts journal specific data and saves to csv files by journal.

Cleaning Data from PubMed

1. PubMed_Genderize.R

   • Genderize first names of all the extracted journals with the genderizeR package.

2. PubMed_JoinData.R

   • Joins the genderized first name data with the journal data.

Figure 1 - Scatter plot of percent female authors as a function of impact factor by journal

1. Figure1_CleanImpactFactor.R

   • Extracts specified journal impact factors from the Thomas Reuters Impact Factor data

2. Figure1_Scatter.R

   • Plots and saves Figure 1 sctatter plots. Contains two graphs: percent female authors as a function of impact factor for first and last authorship positions. Also plots the legend.

Figure 2 - Line plot of average percent female authors as a function of year

1. Figure2_CalculateLineData.R

   • Calculates the average percent female author as a function of year by journal. Also combines data with NIH RO1 Grant Award Percentage data.

2. Figure2_Lineplot.R

   • Plots and saves Figure 2 line plots. Contains two graphs: average percent female authors as a function of year for first and last authorship positions.

Table 1 - Calculates the slope of percent female authors as a function of impact factor by journal

1. Table1_Slopes.R
   • Calculates Table 1. Contain a table of slopes of percent female authors as a fucntion of impact factor by journals for first and last authorship positions. Also plot and saves supplementary figure 1 (a figure for table 1).