This study examines the diversity paradox in the context of scientific innovation and career success. Previous research has shown that while diversity promotes innovation, underrepresented groups within organizations often have less successful careers. The researchers aim to determine if this paradox also applies to scientists by analyzing a dataset of approximately 1.2 million US doctoral recipients from 1977 to 2015. To detect scientific innovations, the researchers utilize Structural Topic Models (STMs), which are commonly used to identify latent thematic dimensions in large text corpora. They fit topic models at various levels (K = [50-1000]) and find that fit metrics plateau at K = 400, 500, and 600. They extract concepts by identifying terms of relative importance within each latent theme using the STM output. The researchers explore three weighing schemes for extracting top terms: equally balancing frequency and exclusivity (50/50), attaching more weight to frequency and less to exclusivity (75/25), and attaching more weight to exclusivity and less to frequency (25/75). They conduct sensitivity analyses on nine hyperparameter scenarios and report results where frequency and exclusivity are equally balanced at K = 500. The dataset includes doctoral abstracts from 1982-2010 as input documents for assessing students' scholarship at the beginning of their careers. Year fixed-effects account for left- and right-censoring, enabling comparisons within years. Using extracted scientific concepts, co-occurring concepts in abstracts are aggregated each year to identify students who introduce novel links. Spurious links are removed by computing a significance score based on the log-odds ratio of link occurrence probability compared to component concept term occurrence probabilities independently over the corpus. The outcome variable is measured as novelty and impactful novelty in text. The researchers filter for meaningful links using top FREX terms from structural topic models and remove spurious links through a link significance score. If a link is introduced by two students, it indicates that the concept is novel and impactful. The results show that underrepresented groups produce higher rates of scientific novelty. However, their novel contributions are undervalued and less likely to be taken up by other scholars compared to contributions from gender and racial majorities. Additionally, equally impactful contributions from underrepresented groups are less likely to lead to successful scientific careers compared to majority groups.
- Diversity paradox in scientific innovation and career success
- Previous research shows diversity promotes innovation but underrepresented groups have less successful careers
- Study analyzes dataset of 1.2 million US doctoral recipients from 1977 to 2015
- Structural Topic Models (STMs) used to detect scientific innovations
- Fit metrics plateau at K = 400, 500, and 600 for topic models
- Three weighing schemes for extracting top terms: equal balance, more weight to frequency, more weight to exclusivity
- Sensitivity analyses conducted on nine hyperparameter scenarios
- Dataset includes doctoral abstracts from 1982-2010 as input documents for assessing students' scholarship
- Year fixed-effects account for left and right-censoring for comparisons within years
- Co-occurring concepts in abstracts aggregated each year to identify students introducing novel links
- Spurious links removed using significance score based on log-odds ratio of link occurrence probability compared to component concept term occurrence probabilities independently over the corpus
- Outcome variable measured as novelty and impactful novelty in text
- Underrepresented groups produce higher rates of scientific novelty but contributions undervalued and less likely to be taken up by other scholars compared to majority groups.
- Equally impactful contributions from underrepresented groups less likely to lead to successful scientific careers compared to majority groups.
Summary- Diversity is important for making new and different things in science, but some groups of people don't have as much success in their careers.
- A study looked at a lot of information about 1.2 million people who got their doctorate degrees in the US between 1977 and 2015.
- They used a special way to find out what new ideas were being talked about in science.
- They found that there were certain numbers where the measurements stopped changing much when they looked at the new ideas.
- They also tried different ways to figure out which words were most important in the new ideas.
Definitions
- Diversity: having many different kinds of people or things
- Scientific innovation: coming up with new and different ideas in science
- Career success: doing well and being successful in your job or profession
- Dataset: a collection of information or data
- Doctoral recipients: people who have earned a doctorate degree (the highest level of education)
- Structural Topic Models (STMs): a special method used to find out what topics are being talked about in a large amount of text
Exploring the Diversity Paradox in Scientific Innovation and Career Success
In recent years, organizations have become increasingly aware of the need to promote diversity within their ranks. While research has shown that diversity can lead to increased innovation, underrepresented groups often experience less successful careers than their majority counterparts. This phenomenon is known as the “diversity paradox” and it raises questions about how organizations can foster a more equitable workplace.
This study seeks to explore this paradox in the context of scientific innovation and career success by analyzing a dataset of approximately 1.2 million US doctoral recipients from 1977 to 2015. The researchers utilize Structural Topic Models (STMs) to detect scientific innovations within the data set, extracting concepts by identifying terms of relative importance within each latent theme using STM output. They then filter for meaningful links using top FREX terms from structural topic models and remove spurious links through a link significance score.
Structural Topic Models (STMs)
The researchers fit topic models at various levels (K = [50-1000]) and find that fit metrics plateau at K = 400, 500, and 600. To extract concepts from these topics, they use three different weighing schemes: equally balancing frequency and exclusivity (50/50), attaching more weight to frequency and less to exclusivity (75/25), or attaching more weight to exclusivity and less to frequency (25/75). They conduct sensitivity analyses on nine hyperparameter scenarios with results reported where frequency and exclusivity are equally balanced at K = 500.
Measuring Scientific Innovation
To measure scientific innovation, the researchers use doctoral abstracts from 1982-2010 as input documents for assessing students' scholarship at the beginning of their careers. Year fixed-effects account for left-and right-censoring enabling comparisons within years. Co-occurring concepts in abstracts are aggregated each year to identify students who introduce novel links; if two students introduce a link it indicates that concept is novel and impactful enough for others scholars take up its study further down the line.. The outcome variable is measured as novelty & impactful novelty in text which helps determine whether contributions from underrepresented groups are valued or not compared with those from gender & racial majorities..
Results
The results show that underrepresented groups produce higher rates of scientific novelty but their contributions are often undervalued compared with those made by gender & racial majorities; even when equally impactful contributions are made by minority groups they tend not be taken up leading them having less successful careers than majority group members..
Conclusion
This research demonstrates how organizations must strive towards creating an equitable workplace where all individuals regardless of race or gender have equal opportunities for career success while also promoting innovative ideas which will benefit everyone involved.. Organizations should focus on providing resources such as mentorship programs which help minority groups develop skills necessary for achieving success without sacrificing creativity & originality..
