mteb/BrightProPsychologyRetrieval huggingface dataset:
In addition, some studies have found that gender bias in the early education
stage has a long-term impact on the development of students (Lavy and Sand 
2018 : 263–279.") ), but it is not clear how the impact will change
dynamically, that is, whether the impact will change with the advancement of
age or school grade. Given that the gender gap in mathematics shows a change
from girls leading in elementary school to boys leading in middle school, we
hypothesize that the impact of gender bias will increase with the advancement
of age or school grade and propose the following assumption.
The analysis shows that self-stereotypes and parents’ stereotypes in
mathematics learning will hinder the development of mathematical capability,
and these negative effects tend to increase with the advancement of age or
grade. Males are the beneficiaries of gender stereotypes. However, although
the parents’ gender attitude toward mathematics learning will affect the
performance of their children's mathematical capability, the son’s preference
in the local fertility culture or the existence of brothers in the family has
no significant impact on girls' mathematical capability, which indicates that
there is a positive change in the resource allocation of Chinese society and
families moving toward the trend of “son preference without daughter
discrimination.” Optimistically, value and social changes are inevitable as
China transforms from materialism to the postmaterialist era. However, value
and social changes may lag behind economic changes, and sometimes, they can
only be realized by intergenerational population replacement (Inglehart et al.
 2017 : 1313–1340.") ). Therefore, time is needed
to accumulate positive changes in the social attitude toward females’
mathematics learning or females’ self-pursuit and breakthrough in mathematics
and other natural sciences learning.
Unpacking the structure of research teams to understand whose work is not
recognized requires identifying each individual on each research team,
characterizing their position by their job title, and then determining whether
or not they are named on the articles and patents produced by the research
team. Administrative data can be used to provide highly granular information
about who works on which research project because records in human resources
both document every payment that is made during each pay period from each
grant and provide information on each employee’s job title. Currently, 118
campuses from 36 participating universities provide their deidentified data to
the Institute for Research on Innovation and Science at the University of
Michigan, which processes and standardizes the information as analytical files
 16 .") . The earliest year for which data were provided by a
participating institution was 2000 and the latest was 2019, and the data
include information on payments of wages from individual grants to all people
employed by each grant, including information on the job title for which a
person is paid on a particular grant (Methods, ‘Construction of administrative
data’).
The absence of women in science and technology will weaken their scientific
and technological power and influence on future society. As science and
technology are rapidly changing, people have profoundly realized that science
and technology are the primary sources of productivity. Not only is the
competition for science and technology between countries in full swing, but
all regions in China are also competing to attract science and technology
talent. However, the cultivation of talent comes first, and the cultivation of
science and technology talent occurs in the field of education. Many Western
countries have promoted science, technology, engineering, and mathematics
(STEM) to the level of national strategy and have promulgated a series of
policies to promote STEM education (Wang  2017
 ).
*  Gender difference 
*  Mathematical capability 
*  Stereotype 
*  Son preference
* Received  :  29 September 2022
The estimated regression-adjusted gender differences in attribution rates
across job titles and fields, controlling for a wide variety of observable
factors, are reported in Extended Data Tables  5
 and  6
 . Notably, after including controls, the
gender gap remains for all job titles except undergraduates. The gender gap
similarly remains for 9 out of 13 fields for publications and 8 out of 13
fields for patents, after including controls.
###   Americans are more pessimistic than optimistic about many aspects of
the country’s future
In some ways,
the public has a very positive view of STEM jobs, as they compare with jobs in
other sectors. About seven-in-ten Americans (71%) see jobs in STEM as offering
better compensation than jobs in other industries. And, a majority of
Americans (58%) consider STEM jobs to attract more of the brightest, most
qualified young people.
You are reading page  1   Page  2 
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Page  10
* ###  26 October 2023
Teams were constructed around a central PI, their associated grants, and
individuals employed on those grants from 2013–2016. The scientific field of
each team is identified by using the title of all associated grants and
comparing the grants with a pool of text that describes each scientific field
using a ‘wiki-labelling’ approach  17  ,  18  ,  19
.") . Scientific
documents were linked to a team if the article or patent acknowledged one of
the team’s grants and/or any member of the team was listed as an author on
that article or patent (further details in Methods, ‘Construction of
administrative data’).
However, Fig.  1  (left) also shows that
the share of actual authorships for women is lower than what would be expected
given their share of potential authorships in each career position. The
difference between the share of potential authorships and actual authorships
for women ranges from 15.72 pp for research staff ( _P_ = 0.0000; two-sided
_t_ -test; test value = −15.81; effect size = 15.72 pp) to 7.09 pp for faculty
members ( _P_ = 0.0000; two-sided _t_ -test; test value = −13.34; effect size
= 7.09 pp) to 5.51 pp for postdocs ( _P_ = 0.0000; two-sided _t_ -test; test
value = −5.08; effect size = 5.51 pp; Extended Data Table  3
 ). These gaps are clearly apparent as
every marker Fig.  1  (left) is below the
diagonal (also see Extended Data Table  3
 and Supplementary Fig.  5
 ).
###   Progress towards the Sustainable Development Goals
* ###   Collaboration between women helps close the gender gap in ice core science
Correspondence to  Guihua Xie  or  Xinyu Liu
 .
###  Topics
###  Control variables
The key finding of this work is that, regardless of the measure of scientific
credit, and despite efforts to standardize credit   15
.") , women are much less likely
than men to be credited with authorship. The results are robust to a variety
of alternative specifications and sample restrictions described in detail in
Supplementary Information, part  1  ,
namely (1) differential accuracy of gender imputation for non-English and
Asian names; (2) differential match quality because of name changes and
frequency; (3) the definition of potential authors, including first and last
authorship; (4) differences by type of research output and the timing of
research output relative to employment; (5) heterogeneity across more
disaggregated fields; (6) sample construction; (7) definition of time working
in laboratories; (8) logistic model; and (9) combinations of robustness
checks.
###  Table of Contents
####  Research teams
Pioneering work
from business school professor  Rosabeth Moss Kanter
 in the
late 1970s drew attention to how the structure of organizations – particularly
the balance of minority and majority groups – can influence experiences in the
workplace.
* Accepted  :  02 April 2023
###  Hypothesis 5
Schools are responsible for transmitting knowledge and shaping students’ value
systems, and teachers are important actors in knowledge transmission and value
shaping. School peer groups also play an important role in educational
attainment and value formation (Palardy  2013
: 714–754.") ; Legewie and DiPrete  2012
: 463–485.") ). Therefore, the gender
views of teachers and peer groups have also become an important starting point
for investigating the gap between men and women in mathematics.
The reasons why
half of college-educated workers with STEM-related training turn to jobs
elsewhere are likely complicated. Among college-educated workers, those who
majored in a health professions field are more likely than those who majored
in other STEM fields to be working in a job directly related to their degree.
About seven-in-ten (69%) women who majored in a health professions field (such
as nursing or pharmacy) are working in a health-related occupation, as are 61%
of men who majored in health professions.
* PMID:  **19883140**
* DOI:   10.1037/a0017364
The evidence presented here is consistent with the notion that gender
differences in science may be self-reinforcing—that the fate experienced by
Rosalind Franklin and others like her discouraged numerous potentially high-
impact researchers from entering science   23
.") . The under-representation of women in faculty
positions may be the result of early discouragement among junior researchers:
women are less likely to be recognized for their contributions—especially on
pivotal projects—and may consequently be less likely to advance in their
careers. Longitudinal work on the progress of women’s careers   24
.") could be furthered by studying these data, which could
provide an empirical link between credit attribution, women’s career
progression and discouragement of early-stage researchers.
* 3124  Altmetric
Enrico G. Berkes & Bruce A. Weinberg
Next: 1. Diversity in the STEM workforce varies widely across jobs
* Published  :  22 June 2022
The Journal of Chinese Sociology
**Open Access** This article is licensed under a Creative Commons Attribution
4.0 International License, which permits use, sharing, adaptation,
distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons licence, and indicate if changes were made. The images or
other third party material in this article are included in the article's
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material. If material is not included in the article's Creative Commons
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exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this licence, visit 
http://creativecommons.org/licenses/by/4.0/
 .
###  Research hypotheses
The survey was sent to individuals who had previously published in academic
research journals identified through their public profiles on ORCID, a
platform in which academic researchers post their educational credentials,
work history and publication records. Information on the survey instrument,
e-mail recruitment, and interview protocols is available in part 3 of the 
Supplementary Information  .
###  Gender attitudes in family and school
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An  Author Correction  to this
article was published on 01 September 2023
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Other notable findings include the following:
#####  Regions & Countries __
1\. Diversity in the STEM workforce varies widely across jobs
  2\. Most Americans believe STEM jobs
pay better, but few see them as offering more flexibility for family time
  3\. Women in STEM see more gender disparities at work, especially
those in computer jobs, majority-male workplaces
  4\. Blacks in STEM jobs are especially concerned about
diversity and discrimination in the workplace

 5\. Most Americans evaluate STEM education as middling compared with other
developed nations   6\. Many Americans say they liked
math and science in school, thought about a STEM career
 
Acknowledgments   Methodology   Appendix: Detailed tables and charts
There is a well-documented gap between the observed number of works produced
by women and by men in science, with clear consequences for the retention and
promotion of women   1 .") . The gap might be a result of productivity differences  2  ,  3
,  4  ,  5 .")
, or it might be owing to women’s contributions not being acknowledged   6
.") ,  7
.") . Here we find that at least part of this gap is the
result of unacknowledged contributions: women in research teams are
significantly less likely than men to be credited with authorship. The
findings are consistent across three very different sources of data. Analysis
of the first source—large-scale administrative data on research teams, team
scientific output and attribution of credit—show that women are significantly
less likely to be named on a given article or patent produced by their team
relative to their male peers. The gender gap in attribution is present across
most scientific fields and almost all career stages. The second source—an
extensive survey of authors—similarly shows that women’s scientific
contributions are systematically less likely to be recognized. The third
source—qualitative responses—suggests that the reason that women are less
likely to be credited is because their work is often not known, is not
appreciated or is ignored. At least some of the observed gender gap in
scientific output may be owing not to differences in scientific contribution,
but rather to differences in attribution.
###  Construction of administrative data
However, a study conducted in China on students majoring in science and
technology found that the results of mathematics tests of female students are
higher when they receive negative psychological hints (“male performance is
better than female performance”) than when they receive positive psychological
hints (“female performance is better than male performance”), although the
difference was not statistically significant. The female participants claimed
that “the only effect of being told that male students will do better than
female students in the test is to make them work harder in the test so as to
prove that this prediction is wrong” (Cui and Venator  2008
 ). The authors conjectured that the
“fighting spirit” shown by Chinese women against stereotype threat, as well as
the Chinese only-child policy and the fact that Chinese students are more
accustomed to the pressure of the examination environment, may indicate that
different social and cultural environments shape different social mindsets.
Thus, whether stereotype threat theory in mathematics learning applies to
Chinese females needs further verification.
Compared with those in non-STEM jobs, women in STEM are more likely to say
they have experienced discrimination in the workplace (50% vs. 41%). But in
other respects, the challenges women in STEM face in the workplace echo those
of all working women. Women in STEM and non-STEM jobs are equally likely to
say they have experienced sexual harassment at work, and both groups of women
are less inclined than men to think that women are “usually treated fairly”
when it comes to promotions where they work.
* Career Choice*
There are wide differences among STEM workers on the role of racial/ethnic
discrimination in underrepresentation. Among blacks in STEM jobs, 72% say
discrimination in recruitment, hiring and promotions is a major reason behind
the underrepresentation of blacks and Hispanics in these jobs. By contrast,
27% of whites and 28% of Asians say this, while 43% of Hispanics think
discrimination is a major reason behind the underrepresentation.
###   Scientific authorship by gender: trends before and during a global
pandemic
These findings come amid heightened public debate about  underrepresentation
 and treatment of women
– as well as racial and ethnic minorities – in the fast-growing technology
industry and decades of concern about how best to promote diversity and
inclusion in the STEM workforce. Conducted in the summer of 2017, prior to the
recent outcry about sexual harassment by men in positions of public
prominence, the Center’s new survey findings also speak to the broader issues
facing women in the workplace across occupations and industries.  1
###   Americans’ Views of the Israel-Hamas War
* Issue Date  :  04 August 2022
* Sex Characteristics*
###  Hypothesis 2
###   Gender bias in Nobel prizes
Gender is algorithmically assigned using a combination of Ethnea   32
.") ,  40 .") and the
Python Gender Guesser algorithms. Ethnea is first used to assign gender based
on the first name and ethnicity (algorithmically assigned from the family
name) of each employee. When the first name gives ambiguous results, the
middle name is used. If gender is still ambiguous, Python’s Gender Guesser is
applied to the individual’s first name, but not the middle name. Gender can be
identified for 107,239 people (83.2% of sample), of whom 51,738 are women and
55,502 are men.
5. Bruce A. Weinberg
This article has been  updated
* Published  :  22 May 2023
In addition to the open-ended text field in which researchers could record
their experiences, the last question of the survey solicited researchers “to
interview over Zoom regarding their experiences with the allocation of credit
in research teams.” Respondents were told that if they were interested in
talking about their experiences with the allocation of scientific credit on
teams, they could enter their e-mail addresses to be contacted for a follow-up
interview. A team of two authors (of both genders for three interviews, and of
one gender for three interviews) of this paper interviewed six individuals for
30 min each. Four were women and two were men. Gender was never raised as an
issue by the team but was raised by the interviewees. The detailed interview
protocol is available in Supplementary Information, part  3
 .
The first round of the survey collected 19,487 valid student questionnaires
(including 10,279 in the seventh grade) and the corresponding questionnaires
of parents, teachers, and school leaders (see Wang  2016
 for
details). The second and third rounds of the survey, respectively, tracked
down 9920 and 8862 former seventh-grade students (including newly transferred
students) and their families, teachers, and school leaders. This study focuses
on the performance of mathematical capability in the three years of learning
(grades 7/8/9) and the changes during this period. Therefore, only the samples
of the classes of 2013 (grade 7) are retained. After the samples with missing
variables were eliminated, the three rounds of surveys obtained 9939 student
samples, with a total of 26,903 analysis samples. The data structure is
school/grade.
The third measure reflects the fact that not all scientific documents are
created equal. The omission of Franklin from the Crick and Watson paper was
particularly egregious because of its high potential and ultimate scientific
impact. The empirical implementation of the third measure is to attach forward
citations to the articles and patents. Figure  3
 shows that, when controlling for field,
career position and team size, there is no significant difference between the
likelihood of a woman being named relative to a man on an article with zero
citations ( _P_ = 0.1725; two-sided _t_ -test; test value = 1.3642; effect
size = 0.1392 pp). However, for more highly cited articles women are less
likely than men to be named. For example, on an article with 25 citations
women are 19.9739% less likely to be named than men relative to the baseline (
_P_ < 0.0001; two-sided _t_ -test; test value = −7.4982; effect size = 0.6352
pp; Extended Data Table  7  ).
####  Patents
*  Computer science work and interest profiles: stereotype vs. realities.
Another valuable finding of this study is that the CEPS data show that junior
high school girls in China are not affected by stereotype threat. Western
psychological studies suggest that the gender stereotype of mathematics
learning could apply to female individuals in two ways: the first is the
internalization of ideas through the process of socialization, which affects
the individual’s behavior; the second is the contextual pressure on females,
which causes inconsistent performance of women in competition and gradually
diminishes their confidence, interest, and motivation in further learning.
Some researchers have proposed same-gender mathematics classroom education
(Niederle and Lise  2010 :
129–144.") ). However, in China, neither the female college students
participating in the experiment (Cui and Venator  2008
 ) nor the female junior high school
students in the present survey when facing the explicit or implicit gender-
biased situation/atmosphere, show the trend of “the greater the pressure is,
the stronger they are.”  Footnote  21  This may, to some extent, indicate that
for the females participating in these surveys, their reaction patterns to
gender bias may differ fundamentally from those of females under other
cultural traditions. This finding also means that we should further verify
relevant theories and explore the boundaries of the theoretical applications
and the impacts behind them.
In addition to traditional social and cultural views of gender stereotypes,
factors affecting women's mathematics learning include gender equality in
countries or regions (Penner  2008
: S138–S170.") ; Guiso et al.  2008
 ). Chinese society has a far-reaching and longstanding tradition
of male superiority and son preference. Even though the slogan “women can hold
up half the sky” has been put forward in China since the 1950s to promote
equality between men and women in education, occupation, and other aspects,
the traditional preference for sons has not been completely transformed from
the perspective of family reproduction. The problem of gender ratio deviation
has been included in the 13th five-year plan of the National Health
Commission.  Footnote  7
Women are often besieged by stereotypical remarks and views, such as “women
are not good at math/science,” throughout their years of education. People
believe that women are good at linguistics, history, and similar art subjects
that hinge on the capability of language or memory, while men are good at
math, physics, and similar science subjects that require logical reasoning. If
a girl performs well in math in elementary school, she is often told that
“girls will not be good at learning math when they enter middle school.” If
the girl continues to perform well in middle school, she is often told that
“women are not suitable for science studies.” The results obtained from real-
world observations also confirm these perceptions. In mathematics, female
students score higher than male students in elementary school, but this gender
gap narrows or even disappears in junior high school, and the math scores of
male students become significantly higher than those of female students in
senior high school (Wu  2016  ). In other words, there has never been a fundamental change in the
gender gap in science subjects in high school.
* Vocational Guidance
Research Topics
Rong Su  et al.  Psychol Bull  .  2009 Nov  .
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