VS Field Study Follow-up Report

Study Information

Dataset description Description in R # of Observations
Raw dataset full_data_raw 390
Raw dataset w/ gender-diverse pairs full_data_raw_gender_diverse 65
Dataset filtered on 1 nearest attn check full_data_nattn 178
Dataset filtered on 1 nearest attn check and gender-diverse pairs full_data_nattn_gender_diverse 46
Dataset filtered on all three attention checks full_data_fullclean 166
Dataset filtered on all three attention checks and gender-diverse pairs full_data_fullclean_gender_diverse 43

Measures

Key

Measure Rater Rated Description in R
Supervisor-rated Voice Quality Supervisor Focal Employee/Coworker supervisor_voice_quality
Supervisor-rated Employee’s Needs Supply Fit Supervisor Focal Employee/Coworker supervisor_needs_supply
Supervisor-rated Employee’s Demands-Abilities Fit Supervisor Focal Employee/Coworker supervisor_demands_abilities
Employee’s ratings of Supervisor’s Voice Solicitation Focal Employee/Coworker Supervisor self_voice
Employee’s self ratings of voice quality Focal Employee/Coworker Focal Employee/Coworker self_voice_quality
Employee’s self ratings of Demands-Abilities Fit Focal Employee/Coworker Focal Employee/Coworker self_demands_abilities
Employee’s self ratings of Needs-Supplies Fit Focal Employee/Coworker Focal Employee/Coworker self_needs_supply
Employee’s self ratings of expertise Focal Employee/Coworker Focal Employee/Coworker self_expertise
Supervisor Gender Supervisor s_gender_f
Employee Gender Focal Employee/Coworker employee_gender_f

Items

All items will be measured on a scale from 1 (Not at all) to 7 (Very much so).

Supervisor-rated Items.

Supervisor-rated Voice Quality.
To what extent do you agree or disagree with the following statements in regard to (Focal employee/Coworker)’s ability to address sexism in the workplace?
1. They can offer useful ideas.
2. Their ideas will likely have a lot of value for improving sexism.

Supervisor-rated Employee’s Needs Supply Fit.
To what extent do you agree or disagree with the following statements in regard to (Focal employee/Coworker)?
1. There is a good fit between what addressing sexism at our organization offers (Focal employee/Coworker) and what (Focal employee/Coworker) is looking for in a job.
2. The attributes that (Focal employee/Coworker) looks for in a job are fulfilled very well by addressing sexism at our organization.
3. Addressing sexism at our organization gives (Focal employee/Coworker)much of what they want from a job.

Supervisor-rated Employee’s Demands Abilities Fit.
To what extent do you agree or disagree with the following statements in regard to (Focal employee/Coworker)’s ability to address sexism in the workplace?
1. There is a good match between addressing sexism and (Focal employee/Coworker)’s personal skills.
2. (Focal employee/Coworker)’s abilities are a good fit with the requirements of addressing sexism.
3. (Focal employee/Coworker)’s personal abilities provide a good match with the demands of addressing sexism.

Employee-rated Items.

Employee’s Ratings of Supervisor’s Voice Solicitation.
In terms of your supervisor, to what extent do you agree with the following statements?
They would personally come to me to ask about…
1. things that I think would be helpful for reducing sexism, or improving gender equality, in this organization.
2. how I have previously addressed sexism at work.
3. knowledge related to sexism.
4. what skills I have that they may not know about that might contribute to reducing sexism or improving gender equality in this organization.

Employee-rated Employee’s Needs Supply Fit.
To what extent do you agree with the following statements:
1. There is a good fit between what addressing sexism at my organization offers for me and what I am looking for in a job.
2. The attributes that I look for in a job are fulfilled very well by addressing sexism at our organization.
3. Addressing sexism at our organization gives me just about everything that I want from a job.

Employee-rated Employee’s Demands Abilities Fit.
To what extent do you agree with the following statements?
1. There is a good match between addressing sexism at my organization and my personal skills
2. My abilities are a good fit with the requirements of addressing sexism
3. My personal abilities provide a good match with the demands of addressing sexism.

Employee-rated Voice Quality.
To what extent do you agree or disagree with the following statements in regard to your ability to address sexism in the workplace?
1. I can offer useful ideas.
2. My ideas will likely have a lot of value for improving sexism.

Employee-rated Expertise.
Do you have formal education in implementing any of the following (1 = None at all, 4 = Some, 7 = Very much):
1. Planning or implementing anti-sexism trainings.
2. Planning or implementing programs or policies that enhance gender equality.
3. Confronting sexist behaviors.

Analyses

Does employee gender predict our DVs?

Note: For all of these analyses, the reference level is “woman”. So the coefficient estimates compare if the employee is a man relative to the woman.

Raw Data

Raw Data Filtered for Gender Diverse Pairs

Nearest Attention Check Data

Nearest Attention Check Data With Gender Diversity

Full Attention Check Data

Full Attention Check Data W/ Gender Diverse Pair

Does gender diversity moderate our results?

Note: The below analyses specify whether the focal-employee/coworker pair is gender diverse (1) or not (0) as the moderator. I include the graphs in the following section so that it is easier to compare consistent results across analyses.

Overall Analyses

Raw Data

Nearest Attention Check

Full Attention Check

Graphs

Raw Data: The pair’s gender diversity moderated the employee’s self-rated voice quality and self-rated needs-supply fit.

Self-rated Voice Quality

Self-rated Needs-Supply Fit

Nearest Attention check: the pair’s gender diversity moderated the employee’s self-rated voice quality and self-rated needs-supply fit.

Self-rated Voice Quality

Self-rated Needs-Supply Fit

Full Attention Check: the pair’s gender diversity moderated the employee’s self-rated voice quality. There was a marginal moderation on the employee’s self-rated needs-supply fit and self-rated expertise.

Self-rated Voice Quality

Self-rated Needs-Supply Fit

Self-rated Expertise

Does supervisor gender moderate our results?

Note: The below analyses specifies the supervisor’s gender as the moderator. I include the graphs in the following section so that it is easier to compare consistent results across analyses.

Raw Data

Raw Data Filtered for Gender Diverse Pairs

Nearest Attention Check

Nearest Attention Check with gender diverse pairs

Full Attention Check

Full Attention Check With Gender Diverse Pairs

Graphs

Men with female supervisors rated themselves as having higher voice quality than men with male sueprvisors or women!

Full data raw

Full data filtered for gender-diverse pairs

Filtered on nearest attention check

Filtered on nearest attention check, and with gender-diverse pairs

Filtered on all attention checks

Filtered on nearest attention check, and with gender-diverse pairs

Moderation Analyses Across DVs

I included graphs in the section below. I did not include graphs, here, so that it would be easier to see which moderation results were consistent across analyses.

Raw Data

Raw Data with Gender Diverse Pairs

Nearest Attention Check Data

Nearest Attention Check Data with Gender Diverse Pairs

Full Attention Check

Full Attention Check with Gender Diverse Pairs

Graphs

Raw Data

Participants with higher levels of self-reported demands abilities believed they had higher needs-supply fit. It looks like there is a stronger relationship with men, relative to women.

Raw Data with Gender Diverse Pairs

Participants with higher levels of self-reported voice quality believed they had higher demands-abilities fit. It looks like there is a stronger relationship with women, relative to men.

Participants with higher levels of self-reported expertise believed they had higher demands-abilities fit. It looks like there is a stronger relationship with women, relative to men.

Participants with higher levels of self-reported expertise believed they had higher voice quality It looks like there is a stronger relationship with women, relative to men.

Nearest Attention Check Data

Participants with higher levels of self-reported demands-abilities fit had higher self-rated expertise. It looks like there is a stronger relationship with women, relative to men.

Nearest Attention Check Data with Gender Diverse Pairs

Full Attention Check

Full Attention Check with Gender Diverse Pairs

Filtering on just male supervisors

Does employee gender predict our DVs?

Note: For all of these analyses, the reference level is “woman”. So the coefficient estimates compare if the employee is a man relative to the woman.

Raw Data

Raw Data Filtered for Gender Diverse Pairs

Nearest Attention Check Data

Nearest Attention Check Data With Gender Diversity

Full Attention Check Data

Full Attention Check Data W/ Gender Diverse Pair

Does gender diversity moderate our results?

Note: The below analyses specify whether the focal-employee/coworker pair is gender diverse (1) or not (0) as the moderator. I include the graphs in the following section so that it is easier to compare consistent results across analyses.

Overall Analyses

Raw Data
Nearest Attention Check
Full Attention Check

Selected Graphs (on full attention check dataset)