The role of gender in the decision to pursue a surgical career: A qualitative, interview-based study

Background: Previous literature has explored the underrepresentation of women in surgery. However, this research has often been quantitative or limited by considering only the perspectives and experiences of women at more advanced career stages. Here, we use a qualitative methodology and a sample of women and men across the career continuum to identify the role that gender plays in the decision to pursue a surgical career. Methods: We audio-recorded and transcribed semi-structured interviews conducted with 12 women and 12 men ranging in their level of medical training from medical students to residents to staff surgeons. We used Braun and Clarke’s six-step approach to thematic analysis to analyze the data, maintaining trustworthiness and credibility by employing strategies including reflexivity and participant input.  Results: Our findings suggested that the characteristics of surgery and early exposure to the profession served as important factors in participants’ decisions to pursue a surgical career. Although not explicitly mentioned by participants, each of these areas may implicitly be gendered. Gender-based factors explicitly mentioned by participants included the surgical lifestyle and experiences with gender discrimination, including sexual harassment. These factors were perceived as challenges that disproportionately affected women and needed to be overcome when pursuing a surgical career. Conclusions: Our findings suggest that gender is more likely to act as a barrier to a career in surgery than as a motivator, especially among women. This suggests a need for early experiences in the operating room and mentorship. Policy change promoting work-life integration and education to target gender discrimination is also recommended

Gender inference: can chatGPT outperform common commercial tools?

An increasing number of studies use gender information to understand phenomena such as gender bias, inequity in access and participation, or the impact of the Covid pandemic response. Unfortunately, most datasets do not include self-reported gender information, making it necessary for researchers to infer gender from other information, such as names or names and country information. An important limitation of these tools is that they fail to appropriately capture the fact that gender exists on a non-binary scale, however, it remains important to evaluate and compare how well these tools perform in a variety of contexts. In this paper, we compare the performance of a generative Artificial Intelligence (AI) tool ChatGPT with three commercially available list-based and machine learning-based gender inference tools (Namsor, Gender-API, and genderize.io) on a unique dataset. Specifically, we use a large Olympic athlete dataset and report how variations in the input (e.g., first name and first and last name, with and without country information) impact the accuracy of their predictions. We report results for the full set, as well as for the subsets: medal versus non-medal winners, athletes from the largest English-speaking countries, and athletes from East Asia. On these sets, we find that Namsor is the best traditional commercially available tool. However, ChatGPT performs at least as well as Namsor and often outperforms it, especially for the female sample when country and/or last name information is available. All tools perform better on medalists versus non-medalists and on names from English-speaking countries. Although not designed for this purpose, ChatGPT may be a cost-effective tool for gender prediction. In the future, it might even be possible for ChatGPT or other large scale language models to better identify self-reported gender rather than report gender on a binary scale.Comment: 14 pages, 8 table

Letter from the Editor: Special Issue on Difficult Memories and the Museum

This special issue, Difficult Memories and the Museum, aims to extend conversations among and between practitioners and museum studies scholars around how to be intentional and thoughtful in the collection, selection, preservation, arrangement, circulation, and interpretation of cultural artifacts that surface difficult pasts. The articles included here consider museums in Brazil, the United States, the United Kingdom, the Netherlands, Chile, Argentina, and the Dominican Republic and are the product of exchanges between Canadian and Brazilian researchers. I hope in reading this issue, it becomes evident that examining and contending with issues of difficult memories in museums benefits from a global perspective. Museum curation is global in the sense that it is impacted by the movement of individuals, artifacts, and ideas across both temporal and spatial borders

Letter from the Editor

As an academic field, ‘information science’ has repeatedly been characterized as complex and interdisciplinary. When investigating “the properties and behavior of information, the forces governing the flow of information, and the means of processing information,” information science scholars converse with external disciplines (Borko, 1968, p. 3). They borrow theory, adopt frameworks, and apply methodologies from what have been termed ‘content’ or ‘conventional’ disciplines, e.g., mathematics, linguistics, computer science, philosophy, strategic management, psychology, communications, library science (Bates, 1999). Simultaneously, information science practitioners contribute their own insights regarding the organization, representation, form, management, and use of information and information systems in the conventional disciplines. By attending to all the conventional disciplines, information science behaves as a ‘meta-discipline’ (Bates, 1999). This issue aligns with this notion of information science as a ‘meta-discipline’ that is both parallel and perpendicular to conventional disciplines

THE POLITICS AND EVOLUTION OF TIKTOK AS PLATFORM TOOL

A fast-growing international success, ByteDance’s short video platform TikTok is a relevant case study to examine how digital platforms expand infrastructurally and accumulate power. TikTok has achieved popularity comparable to major players, including Facebook, Instagram, and Snapchat. It now grapples with balancing the diverse interests of its different user groups, chief among which content creators. We interrogate how TikTok manages this challenge via an exploratory study that studies the platform’s evolution through what we dub ‘platform tools,’ or, the software-based instruments for cultural production on social media platforms. Such software-based tools have been previously theorized using the ‘boundary resources’ framework, which emerged from information systems studies. This framework conceptualizes platform tools as interrelated, contextual, and dynamic, changing in response to variables internal and external to the platform ecosystem. Recognizing that platform tools are ever-changing, we conduct a ‘platform historiography’ to periodize three main trends: platform tools (1) have contributed to the formalization and professionalization of platform content; (2) have encouraged the standardization of platform-dependent cultural production; and (3) have furthered the platformization of TikTok both within, as well as outside the cultural industries. Our paper serves as a response to calls from media scholars to view platforms as contingent and ever-evolving, and to further social media historiography. More specifically, we contribute to the literature on platform studies because it focuses on an understudied aspect of platform governance: platform tools