Question 1. [Motivation & Research Question] We would love to know more about how this project emerged. How did you start the project? Did your discussions initiate from data, theory, or phenomena?
Data, theory, and phenomenon each mattered as this project took shape, but the phenomenon was our most important starting point. We were PhD colleagues at the University of Maryland, and we spent many hours in Brad’s office discussing research ideas. Like many ASQ readers and contributors, we share an interest in understanding how organizations shape inequality.
The University of Maryland is in the DC area, so we often encountered stories about life on Capitol Hill. A friend of a friend worked as a Congressional aide, and he mentioned that Capitol Hill folk wisdom suggests that Republican officeholders tend to pay their female staff less than their male staff. We had recently seen an article in the AER called “Revolving Door Lobbyists” (i Vidal et al., 2012) that described a data source containing the salaries of all staffers on Capitol Hill. We realized that we could test this folk theory with these data, so Seth used a grant from the Strategic Management Society to buy a cleaned version of the data from a company called Legistorm. This was in late 2012 or early 2013.
We took that folk theory to these data, and sure enough, we found that Republican officeholders tended to pay female staff about 2% less than male staff. We presented these findings in some internal brownbags and at the Wharton People and Organizations conference. We received two pieces of feedback: 1) your data do not contain normal organizations, and 2) you need to build your theorizing on a stronger foundation. We were stumped!
Around this time, we discovered the path-breaking paper by MK Chin, Don Hambrick, and Linda Treviño (2013) in ASQ, about executives’ political ideologies and their CSR investments. This paper created two huge “Eureka!” moments for us.
First, these folks were theorizing *directly* about how leaders’ political ideology might affect their organizational decision-making. In our previous drafts, our theory was very context specific, focusing on the Republican Party and the Democratic Party, rather than their underlying ideologies per se. Suddenly we saw how we could enrich and generalize our arguments, using the theoretical tools that Chin, Hambrick, and Treviño (2013) created.
Second, we realized we could use their approach of measuring political ideology using political donation data. This would allow us to test our predictions outside of Capitol Hill and inside of more typical organizations, using data on law firms that Seth had obtained for another project.
There is no doubt that our project would have languished without all the hard work that MK, Don, and Linda put into their paper. We also learned a lot from other papers on political ideology by Forrest Briscoe, Abhinav Gupta, and Adam Wowak. Our paper stands on the shoulders of these giants!
Funnily enough, the Capitol Hill data from Legistorm does not appear in our final paper. However, early on, we named the shared Dropbox folder that we used for this project “Legistorm,” and that is still how we refer to this project today.
Question 2. [Co-authorship] Brad, you work in an Information & Decision Science department while Seth, your position is in a Strategy department; do you have any advice for students thinking about spanning the boundaries between different business subfields?
In order to be published, a paper that combines two fields still needs to have a well-defined target audience in one field or the other. Do not allow your paper to get “stuck in the middle” by writing the paper towards multiple fields at once. Use the introduction of your paper to clearly identify and speak to the audience that reads the target journal, and then use the discussion section to discuss implications for the other field.
If your field is *not* the one that reads the paper’s target journal, try your best to present the paper to colleagues in your field, especially your own department. Otherwise, these folks might a) miss the paper, or b) attribute the paper to your colleague who traditionally writes for the target journal. The presentation should be at least a little different from the paper, because your presentation should emphasize the interests of the audience from your field, instead of the field for the target journal.
Question 3. [Review Process] How did the paper evolve from the first draft to the published version?
a. During the review process, how did the framing of your paper change over time, if at all?
b. What was some of the push back (if any) that you received?
First, we owe Chris Marquis huge thanks for his editorial guidance. In each round, he gave us a very clear roadmap on how we might address the reviewers’ suggestions. This was critical for us, especially because we were junior researchers who had never published in ASQ.
We also want to use this opportunity to thank the three anonymous reviewers. It is rare that authors get the chance to thank reviewers, but we hope that they read this blog post! Thank you for your clear, consistent, and constructive suggestions. We feel very lucky to have worked with you.
3-a. We think Prof. Marquis and the reviewers would agree that the review process greatly improved the paper. The framing of the paper changed in small but important ways from its first submission. The biggest change was that, in the first submission, we did not have any analysis of the gender of the decision maker. We focused only on the gender of the subordinate. But the reviewers smartly nudged us in this direction.
3-b. We received pushback on two fronts. Theoretically, the reviewers wanted us to differentiate our arguments from those made by authors who had looked at the relationship between employees’ political ideology and the firm’s CSR outcomes. We did this by bringing in Gorman’s (2005) framework for understanding gender inequality inside organizations. She distinguishes between an organization’s interactional and structural mechanisms that produce gender inequality. In our paper, we describe how managers’ political ideology might shape the interactional and structural forces that create gender inequality among their subordinates.
Empirically, the reviewers wanted us to do a better job addressing the possibility that the paper’s results could be driven by a matching process, whereby the best female subordinates purposefully match with liberal supervisors. To help with this issue – though, to be clear, we did not solve it – we obtained some additional data on attorney’s law school accomplishments.
Question 4. [Relationship to Other Paper] In what contexts do you think it is more important to directly measure attitudes towards gender (or proxy by political beliefs) rather than rely on individuals’ gender? For example, in another paper you published together with Laura Huang (Greenwood, Carnahan, and Huang, 2018), you find that the gender match between patient and physician increases survival rates for women patients, and that this effect attenuates when male physicians have more female colleagues or more experience with female patients. While it seems like knowledge, communication skills, or patients’ comfort level likely played a role here, do you think gender stereotypes might have too? And vice versa, do you think the former three factors might play a role in the context of lawyers’ political beliefs and gender inequality?
The sad fact is that most powerful decision makers in organizations are men, so it is important to understand why some male managers may have better outcomes among their female subordinates and female clients than other male managers. Across these two papers, we have some evidence that men with a liberal political ideology and men with more exposure to women colleagues and women clients tend to have better outcomes among their female subordinates and clients. Of course, these are just average effects. One needs to look no further than Harvey Weinstein to find a man who outwardly expresses a liberal political ideology but who engages in egregious misconduct towards female subordinates.
You make a great point: the mechanisms that are at play in this ASQ paper might also be at play in our paper with Laura Huang, and vice versa. Both of these papers took shape around the same time. Our paper with Laura (who, as many ASQ readers will know, is a genius, an inspiration, and a legend) documents that female heart attack patients tend to have better outcomes when their ER doctor is a woman instead of man.
In that paper with Laura, we focused on how male doctors might perform worse with female patients because male doctors might lack knowledge, communication skills, and rapport with female patients. By contrast, our paper in ASQ focuses on how conservative male attorneys might avoid working with and promoting female subordinates because of gender stereotypes: for example, conservative male attorneys might think that female subordinates lack traditional (i.e. masculine) leadership qualities.
Your excellent question underscores an important limitation to both of these papers. We don’t have good empirical measures that capture the underlying mechanisms that link lawyers’ and doctors’ characteristics with our outcomes of interest.
Our fieldwork drove the mechanisms that we emphasize in each paper. The attorneys that we interviewed tended to focus on stereotypes when explaining how their bosses’ politics shaped their careers, whereas the physicians we interviewed emphasized the connection that female patients can form with ER doctors that share their gender. But there’s no doubt that there’s room for all these mechanisms in both settings.
Question 5. [Research Implications] What do you think are the implications, if any, of increasing political polarization on the relationship between managers’ political beliefs and gender inequality? Any thoughts on how the results might look with a more recent sample?
This is rank speculation, but it seems possible that the patterns we see in the paper (which uses a sample from the years 2007-2011) would be even stronger now. Many political scientists point out that the current liberal-conservative divide in the United States seems to be about identity more than economic issues. And the role of gender in our political divide seems to have increased, as evidenced by the Women’s March, #MeToo, and related social movements.
We downloaded some data from the General Social Survey (GSS), which we use in our paper, in order to temper our rank speculation with at least a little bit of quantitative data. Using GSS data, we made a simple plot in Excel. This plot shows the correlation between two variables over time. The first variable captures the self-reported liberalness of a respondent’s political ideology, ranging from extremely liberal to extremely conservative. The second variable captures the respondent’s agreement with the following statement: “Because of past discrimination, employers should make special efforts to hire and promote qualified women.” We see that the correlation between these two variables is at an all-time high in 2018.
Source: General Social Survey
Stata command: bysort year: correlate polviews fehire
Thank you very much for your insightful questions and for your interest in our research!