The social lives of viruses and other mobile genetic elements: a commentary on Leeks et al. 2023.

Illustration of life-histories of phages and plasmids through horizontal and vertical transmission (see Figure 1 for more information).

Language Differences by Race on Letters of Recommendation for the Pediatric Surgery Match.

OBJECTIVE: This study aims to evaluate if there is any significant linguistic difference in LoR based on applicant's race/ethnicity. DESIGN: Retrospective review of applications to pediatric surgery fellowship at a single institution (2016-2020). Race was self-reported by applicants. LoR were analyzed via the Linguistic Inquiry and Word Count (LIWC) software program. SETTING: Johns Hopkins All Children's Hospital, St. Petersburg, Florida USA. A free-standing tertiary pediatric hospital. PARTICIPANTS: Pediatric surgery fellowship applicants from 2016 to 2020. RESULTS: A total of 1086 LoR from 280 applicants (52% female) were analyzed. Racial distribution was Caucasians 62.1%, Asian 12.1%, Hispanics 7.1%, multiracial 6.4% African Americans 5%, and other/unknown 7.1%. Letter writers were largely male (84%), pediatric surgeons (63%) and professors (57%). There was no difference in LoR word count across races. LoR for female multiracial candidates contained higher use of affiliation and negative emotion terms compared to Hispanic females (p = 0.002 and 0.048, respectively), and past focus terms when compared to Caucasian and Asian female applicants (p < 0.001 and p = 0.003, respectively). Religion terms were more common in LoR for Asian females when compared to Caucasian females (p < 0.001). CONCLUSION: This study demonstrates linguistic differences in LoR for pediatric surgery training programs based on applicant race/ethnicity. While differences are present, these do not suggest overt bias based on applicants race or ethnicity.

Examining Implicit Bias Differences in Pediatric Surgical Fellowship Letters of Recommendation Using Natural Language Processing.

OBJECTIVE: We analyzed the prevalence and type of bias in letters of recommendation (LOR) for pediatric surgical fellowship applications from 2016-2021 using natural language processing (NLP) at a quaternary care academic hospital. DESIGN: Demographics were extracted from submitted applications. The Valence Aware Dictionary for sEntiment Reasoning (VADER) model was used to calculate polarity scores. The National Research Council dataset was used for emotion and intensity analysis.  The Kruskal-Wallis H-test was used to determine statistical significance.  SETTING: This study took place at a single, academic, free standing quaternary care children's hospital with an ACGME accredited pediatric surgery fellowship. PARTICIPANTS: Applicants to a single pediatric surgery fellowship were selected for this study from 2016 to 2021. A total of 182 individual applicants were included and 701 letters of recommendation were analyzed. RESULTS: Black applicants had the highest mean polarity (most positive), while Hispanic applicants had the lowest.  Overall differences between polarity distributions were not statistically significant.   The intensity of emotions showed that differences in "anger" were statistically significant (p=0.03).  Mean polarity was higher for applicants that successfully matched in pediatric surgery. DISCUSSION: This study identified differences in LORs based on racial and gender demographics submitted as part of pediatric surgical fellowship applications to a single training program. The presence of bias in letters of recommendation can lead to inequities in demographics to a given program. While difficult to detect for humans, natural language processing is able to detect bias as well as differences in polarity and emotional intensity. While the types of emotions identified in this study are highly similar among race and gender groups, the intensity of these emotions revealed differences, with "anger" being most significant. CONCLUSION: From this work, it can be concluded that bias in LORs, as reflected as differences in polarity, which is likely a result of the intensity of the emotions being used and not the types of emotions being expressed.   Natural language processing shows promise in identification of subtle areas of bias that may influence an individual's likelihood of successful matching.

Letters of recommendation for pediatric surgery fellowship: Analysis of linguistic differences based on gender of the applicant.

BACKGROUND: Gender bias in letters of recommendation (LOR) has been reported for candidate selection in academic medicine, typically with females frequently described with communal terms (e.g. helpful, kind, interpersonal) and males described more with agentic terms (e.g. assertive, intellectual, ambitious). This study examined the presence of linguistic gender differences in LOR for Pediatric Surgery Fellowship. METHODS: LOR submitted to a single pediatric surgery fellowship program between 2014 and 2018 were retrospectively reviewed and analyzed using a previously validated Linguistic Inquiry and Word Count Software (LIWC) program. Descriptive statistics and bivariate analysis were employed in our analysis. Multivariable logistic regression models were built to assess independent association of LIWC variables with applicant gender, LOR writer gender, and applicant-writer gender concordance. RESULTS: 1264 LOR from 325 applicants (51% female) were analyzed. Of the letter writers, 83% were male, 57% were professors, and 7.6% were Pediatric Surgery Fellowship Program Directors. The overall median average word count was 518 words, with no significant difference in LOR word count between applicant genders. Compared to male applicants, female applicants were described significantly more with work words (e.g. excellent, work; p = 0.04). Male LOR writers used authentic words (e.g. honest, humble; p = 0.006) and home words (e.g. family, house; p = 0.04) significantly more than female LOR writers. There were no significant differences in the use of agentic and communal words between genders. CONCLUSION: While there are linguistic differences in LOR for candidates in the Pediatric Surgery match based on gender, previously described overt gender bias was not seen in this study. Interestingly, female candidates were described more with work words, like excellent; a reversal of previously described gender bias in academic medicine. These findings may be due to the unique interpersonal and multidisciplinary skills required in pediatric surgery and may represent a unique form of gender bias that warrants further study.