Sur les frontières de la reconnaissance

Faisant appel aux études récentes portant sur la reconnaissance et l’identité sociale, nous analysons les changements dans la catégorisation de l’identité collective des groupes stigmatisés en Israël, en Irlande du Nord, au Québec et au Brésil. Alors que la littérature sur la reconnaissance tend à présumer une opposition nette entre « nous » et « eux », l’analyse de la littérature empirique démontre la complexification et la multiplication des catégories d’identité. Dans les quatre cas nous avons observé le processus de reconnaissance, en explorant les transformations de la signification des frontières internes et externes de l’identité collective pour ses membres ainsi que pour ceux qui lui sont extérieurs. Nous soutenons que la nature conditionnelle de la reconnaissance devrait conduire les chercheurs à considérer non seulement les composantes normatives du conflit ethnique mais aussi, en leur accordant une importance particulière, le langage et la catégorisation qui fondent ce type de débat.On the Boundaries of Recognition. Internal and External Categories of Collective Identity.Drawing upon recent advances in the study of recognition and social identity, we trace changes in the categorization of collective identity among stigmatized groups in Israel, Northern reland, Québec, and Brazil. While the recognition literature commonly assumes an opposition between « Us » and « Them », a review of these empirical cases illustrates the full complexity of identity categories in each of the four cases. We focus on the process of recognition in each case while highlighting the significance of internal and external boundaries of collective identity. We argue that the contingent nature of recognition should lead scholars to consider not only the normative components of ethnic conflict, but more importantly the language and categories which form the basis for such debates.En las fronteras del reconocimiento. Las categorías internas y externas de la identidad colectiva.Fundándonos en estudios recientes sobre el reconocimiento y la identidad social analizamos los cambios de categorización de la identidad colectiva de grupos estigmatizados en Israel, en Irlanda del Norte, en el Québec canadiense y en Brasil. Cuando la literatura sobre reconocimiento presume una oposición neta entre “nosotros” y “ellos” el análisis de los estudios empíricos demuestra la complicación y la multiplicación de las categorías de identidad. En los cuatro casos que hemos observado el proceso de reconocimiento, explorando las transfor­maciones la significación de la las fronteras internas y externas de la identidad colectiva para sus miembros como para los que son exteriores a ella. Consideramos que la naturaleza condicional del reconocimiento debe llevar a los investigadores a analizar no solo a los componentes normativos des conflicto étnico sino también, dándoles una importancia particular, el lenguaje y la categorización que fundan este tipo de debate

An online experiment during the 2020 US-Iran crisis shows that exposure to common enemies can increase political polarization

A longstanding theory indicates that the threat of a common enemy can mitigate conflict between members of rival groups. We tested this hypothesis in a pre-registered experiment where 1670 Republicans and Democrats in the United States were asked to complete an online social learning task with a bot that was labeled as a member of the opposing party. Prior to this task, we exposed respondents to primes about (a) a common enemy (involving Iran and Russia); (b) a patriotic event; or (c) a neutral, apolitical prime. Though we observed no significant differences in the behavior of Democrats as a result of priming, we found that Republicans-and particularly those with very strong conservative views-were significantly less likely to learn from Democrats when primed about a common enemy. Because our study was in the field during the 2020 Iran Crisis, we were able to further evaluate this finding via a natural experiment-Republicans who participated in our study after the crisis were even less influenced by the beliefs of Democrats than those Republicans who participated before this event. These findings indicate common enemies may not reduce inter-group conflict in highly polarized societies, and contribute to a growing number of studies that find evidence of asymmetric political polarization in the United States. We conclude by discussing the implications of these findings for research in social psychology, political conflict, and the rapidly expanding field of computational social science

REFORMS: Reporting Standards for Machine Learning Based Science

Machine learning (ML) methods are proliferating in scientific research. However, the adoption of these methods has been accompanied by failures of validity, reproducibility, and generalizability. These failures can hinder scientific progress, lead to false consensus around invalid claims, and undermine the credibility of ML-based science. ML methods are often applied and fail in similar ways across disciplines. Motivated by this observation, our goal is to provide clear reporting standards for ML-based science. Drawing from an extensive review of past literature, we present the REFORMS checklist ($\textbf{Re}$porting Standards $\textbf{For}$ $\textbf{M}$achine Learning Based $\textbf{S}$cience). It consists of 32 questions and a paired set of guidelines. REFORMS was developed based on a consensus of 19 researchers across computer science, data science, mathematics, social sciences, and biomedical sciences. REFORMS can serve as a resource for researchers when designing and implementing a study, for referees when reviewing papers, and for journals when enforcing standards for transparency and reproducibility

The neutron and its role in cosmology and particle physics

Experiments with cold and ultracold neutrons have reached a level of precision such that problems far beyond the scale of the present Standard Model of particle physics become accessible to experimental investigation. Due to the close links between particle physics and cosmology, these studies also permit a deep look into the very first instances of our universe. First addressed in this article, both in theory and experiment, is the problem of baryogenesis ... The question how baryogenesis could have happened is open to experimental tests, and it turns out that this problem can be curbed by the very stringent limits on an electric dipole moment of the neutron, a quantity that also has deep implications for particle physics. Then we discuss the recent spectacular observation of neutron quantization in the earth's gravitational field and of resonance transitions between such gravitational energy states. These measurements, together with new evaluations of neutron scattering data, set new constraints on deviations from Newton's gravitational law at the picometer scale. Such deviations are predicted in modern theories with extra-dimensions that propose unification of the Planck scale with the scale of the Standard Model ... Another main topic is the weak-interaction parameters in various fields of physics and astrophysics that must all be derived from measured neutron decay data. Up to now, about 10 different neutron decay observables have been measured, much more than needed in the electroweak Standard Model. This allows various precise tests for new physics beyond the Standard Model, competing with or surpassing similar tests at high-energy. The review ends with a discussion of neutron and nuclear data required in the synthesis of the elements during the "first three minutes" and later on in stellar nucleosynthesis.Comment: 91 pages, 30 figures, accepted by Reviews of Modern Physic

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Lost in a random forest: Using Big Data to study rare events

Sudden, broad-scale shifts in public opinion about social problems are relatively rare. Until recently, social scientists were forced to conduct post-hoc case studies of such unusual events that ignore the broader universe of possible shifts in public opinion that do not materialize. The vast amount of data that has recently become available via social media sites such as Facebook and Twitter—as well as the mass-digitization of qualitative archives provide an unprecedented opportunity for scholars to avoid such selection on the dependent variable. Yet the sheer scale of these new data creates a new set of methodological challenges. Conventional linear models, for example, minimize the influence of rare events as “outliers”—especially within analyses of large samples. While more advanced regression models exist to analyze outliers, they suffer from an even more daunting challenge: equifinality, or the likelihood that rare events may occur via different causal pathways. I discuss a variety of possible solutions to these problems—including recent advances in fuzzy set theory and machine learning—but ultimately advocate an ecumenical approach that combines multiple techniques in iterative fashion

Using Internet search data to examine the relationship between anti-Muslim and pro-ISIS sentiment in U.S. counties

Recent terrorist attacks by first- and second-generation immigrants in the United States and Europe indicate that radicalization may result from the failure of ethnic integration-or the rise of intergroup prejudice in communities where home-grown extremists are raised. Yet, these community-level drivers are notoriously difficult to study because public opinion surveys provide biased measures of both prejudice and radicalization. We examine the relationship between anti-Muslim and pro-ISIS (Islamic State of Iraq and Syria) Internet searches in 3099 U.S. counties between 2014 and 2016 using instrumental variable models that control for various community-level factors associated with radicalization. We find that anti-Muslim searches are strongly associated with pro-ISIS searches-particularly in communities with high levels of poverty and ethnic homogeneity. Although more research is needed to verify the causal nature of this relationship, this finding suggests that minority groups may be more susceptible to radicalization if they experience discrimination in settings where they are isolated and therefore highly visible-or in communities where they compete with majority groups for limited financial resources. We evaluate the validity of our findings using several other data sources and discuss the implications of our findings for the study of terrorism and intergroup relations, as well as immigration and counterterrorism policies