scholarly journals Does Race and Gender Inequality Impact Income Growth?

2021 ◽  
Author(s):  
Gustavo A. Marrero ◽  
Juan Gabriel Rodríguez ◽  
Roy van der Weide
Keyword(s):  
Gender Inequality ◽  
Income Growth ◽  
Race And Gender ◽  
And Gender

The Millennial/Gen Z Leftists Are Emerging: Are Sociologists Ready for Them?

2020 ◽  
Vol 63 (3) ◽  
pp. 408-427
Author(s):  
Elaine Bell Kaplan
Keyword(s):  
Social Change ◽  
Gender Inequality ◽  
Status Quo ◽  
Social Scientists ◽  
Race And Gender ◽  
The Status ◽  
And Gender ◽  
The 1960S ◽  
New Generation ◽  
Do So

Sociology is being challenged by the new generation of students and scholars who have another view of society. Millennial/Gen Zs are the most progressive generation since the 1960s. We have had many opportunities to discuss and imagine power, diversity, and social change when we teach them in our classes or attend their campus events. Some Millennial/Gen Z believe, especially those in academia, that social scientists are tied to old theories and ideologies about race and gender, among other inconsistencies. These old ideas do not resonate with their views regarding equity. Millennials are not afraid to challenge the status quo. They do so already by supporting multiple gender and race identities. Several questions come to mind. How do we as sociologists with our sense of history and other issues such as racial and gender inequality help them along the way? Are we ready for this generation? Are they ready for us?

scholarly journals Systemic inequalities for LGBTQ professionals in STEM

2021 ◽  
Vol 7 (3) ◽  
pp. eabe0933
Author(s):  
E. A. Cech ◽  
T. J. Waidzunas
Keyword(s):  
Gender Inequality ◽  
Education Level ◽  
Representative Survey ◽  
Work Effort ◽  
Job Commitment ◽  
Race And Gender ◽  
Professional Societies ◽  
Science Technology ◽  
And Gender ◽  
Employment Sectors

Researchers have documented race and gender inequality in science, technology, engineering, and math (STEM) for decades. Do lesbian, gay, bisexual, transgender, and queer (LGBTQ) professionals face parallel experiences of disadvantage in STEM? Using representative survey data from 21 STEM professional societies (Nsample = 25,324; NLGBTQ = 1006), this paper presents multidimensional and methodologically robust documentation of 5 dimensions of LGBTQ inequality in STEM. Controlling for variation by demographic, discipline, and job factors, LGBTQ STEM professionals were more likely to experience career limitations, harassment, and professional devaluation than their non-LGBTQ peers. They also reported more frequent health difficulties and were more likely to intend to leave STEM. These trends were similar across STEM disciplines and employment sectors. We found no differences by LGBTQ status in education level, work effort, or job commitment. These findings reveal LGBTQ status as a clear axis of inequality in STEM and motivate further research into the mechanisms producing such outcomes.

Referral Patterns for Youths Identified at Risk for Suicide by Trained Gatekeepers

Crisis ◽  
2012 ◽  
Vol 33 (2) ◽  
pp. 113-119 ◽  
Author(s):  
Michael S. Rodi ◽  
Lucas Godoy Garraza ◽  
Christine Walrath ◽  
Robert L. Stephens ◽  
D. Susanne Condron ◽  
...  
Keyword(s):  
Suicide Prevention ◽  
Demographic Characteristics ◽  
Service Access ◽  
Referral Patterns ◽  
Race And Gender ◽  
Lee Smith ◽  
Prevention Behavior ◽  
Key Variables ◽  
And Gender ◽  
To Receive

Background: In order to better understand the posttraining suicide prevention behavior of gatekeeper trainees, the present article examines the referral and service receipt patterns among gatekeeper-identified youths. Methods: Data for this study were drawn from 26 Garrett Lee Smith grantees funded between October 2005 and October 2009 who submitted data about the number, characteristics, and service access of identified youths. Results: The demographic characteristics of identified youths are not related to referral type or receipt. Furthermore, referral setting does not seem to be predictive of the type of referral. Demographic as well as other (nonrisk) characteristics of the youths are not key variables in determining identification or service receipt. Limitations: These data are not necessarily representative of all youths identified by gatekeepers represented in the dataset. The prevalence of risk among all members of the communities from which these data are drawn is unknown. Furthermore, these data likely disproportionately represent gatekeepers associated with systems that effectively track gatekeepers and youths. Conclusions: Gatekeepers appear to be identifying youth across settings, and those youths are being referred for services without regard for race and gender or the settings in which they are identified. Furthermore, youths that may be at highest risk may be more likely to receive those services.

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