FORUM: COVID-19 and IR Scholarship: One Profession, Many Voices
Bibliographic record
Abstract
Abstract The COVID-19 pandemic has affected virtually every aspect of life, for individuals, communities, nations, regions, and the international system. In this forum, scholars from around the world with diverse areas of expertise consider the contributions of international relations (IR) scholarship in our understanding of the politics and governance challenges surrounding the pandemic. The seven essays that follow together examine how our current state of knowledge speaks to the theme of ISA 2020: “Multiple Identities and Scholarship in a Global IR: One Profession, Many Voices.” Each essay features a research area and body of scholarship that both informs our understanding of the COVID-19 pandemic and reflects on how the pandemic challenges us to push our scholarship and intellectual community further. Together, these essays highlight the diversity of our discipline of IR and how its many voices may bring us together in one conversation. La pandemia de COVID-19 ha afectado prácticamente a todos los aspectos de la vida para las personas, las comunidades, las naciones, las regiones y el sistema internacional. En este foro, los académicos de todo el mundo con diversas áreas de experiencia consideran las contribuciones de los estudios de las relaciones internacionales (International Relations, IR) a nuestro entendimiento de la política y los desafíos de gobierno que rodean a la pandemia. Los siete ensayos a continuación analizan en conjunto cómo nuestro estado de conocimiento actual aborda el tema de la Asociación de Estudios Internacionales (International Studies Association, ISA) de 2020: “Múltiples identidades y estudios en una IR global: una profesión, muchas voces.” Cada ensayo presenta un área de investigación y un cuerpo de estudios que conforman nuestro entendimiento de la pandemia de COVID-19 y también reflexionan sobre cómo esta nos desafía a impulsar aún más a nuestra comunidad académica e intelectual. En conjunto, estos ensayos destacan la diversidad de nuestra disciplina de relaciones internacionales y cómo sus numerosas voces pueden juntarnos en una conversación. La pandémie de COVID 2019 a affecté pratiquement tous les aspects de la vie, que ce soit les individus, les communautés, les nations, les régions ou le système international. Dans cette tribune, des chercheurs du monde entier spécialisés dans divers domaines d'expertise réfléchissent aux contributions des recherches en relations internationales à notre compréhension des défis politiques et de gouvernance entourant la pandémie. Les sept essais ainsi réunis examinent la manière dont l’état actuel de nos connaissances aborde le thème de la convention 2020 de l'Association d’études internationales : « Identités et recherches multiples dans des relations internationales globales : une profession, de nombreuses voix ». Chaque essai présente un domaine de recherche et un corpus d’études qui éclaire notre compréhension de la pandémie de COVID 2019 tout en amenant une réflexion sur la façon dont la pandémie nous remet en question et nous pousse à aller plus loin dans nos recherches et notre communauté intellectuelle. Ensemble, ces essais mettent en évidence la diversité de notre discipline des relations internationales et la manière dont ses nombreuses voix peuvent nous réunir dans un débat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.064 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.032 | 0.041 |
| Scholarly communication | 0.040 | 0.031 |
| Open science | 0.004 | 0.025 |
| Research integrity | 0.023 | 0.024 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".