In recent years, both private and public organizations across contexts have begun implementing AI technologies in their recruitment processes. This transition is typically justified by improved efficiency as well as more objective, performance-based ranking, and inclusive selection of job candidates. However, this rapid development has also raised concerns that the use of these emerging technologies will instead increase discrimination or enhance the already existing inequality. In the present study, we first develop the concept of meta-algorithmic judgment to understand how recruiting managers may respond to automation of the hiring process. Second, we draw on this concept in the empirical assessment of the actual consequences of this type of transition by drawing on two large and unique datasets on employment records and job applications from one of Sweden's largest food retail companies. By comparing the outcomes of traditional and algorithmic job recruitment during this technological transition, we find that, contrary to the company's intentions, algorithmic recruitment decreases diversity. However, in contrast to what is often assumed, this is primarily not because the algorithms are biased, but because of what we identify as an unintended human–algorithmic interaction effect.

A critical debate has blossomed within the field of research policy, science and technology studies, and philosophy of science regarding the possible benefits and limitations of allocating extramural grants using a lottery system. The most common view among those supporting the lottery idea is that some form of modified lottery is acceptable, if properly combined with peer review. This means that partial randomization can be applied only after experts have screened the pursuit-worthiness of all submitted proposals and sorted out those of lowest quality. In the present paper, I will argue against the use of partial lotteries or partial randomization and instead promote use of a pure lottery in combination with a radical increase in block funding. The main reason for holding this position is that a partial lottery cannot solve the problems inherent in the current funding system, which is based on grant competitions and peer review. A partial lottery cannot decrease the enormous time-waste, reduce the uneven distribution of time between researchers, neutralize expert biases or mitigate academic power asymmetries. Instead, we need a stronger focus on improving general time management in academia by implementing a more holistic model for organizing research opportunities in the future.

Status as been described as an ancient form of social inequality that interpenetrates modern meritocratic institutions, including research and higher education. Status is a multifaceted social phenomenon that can affect the relations between people in many different ways. Despite political and normative changes that promote equal treatment of men and women, deep-rooted gender biases still exist as integral parts of the creation of status hierarchies in academic life. In this chapter, I illustrate this argument using a number of concrete situations from the Swedish Research Council panel groups in which some male reviewers responded with disrespect to the arguments presented by their female colleagues. The analysis is intended to shed new light on the social dramaturgy of gender-based status inequalities in the grant peer review process. It is unusual in putting the emphasis on the panellists’ detailed interactions rather than on the efforts to encourage gender equality in competition results through rule-changes and other prescriptive means. Moreover, it reveals the intersectionality of gender, age and esteem in shaping the behaviour of panellists.

The purpose of grant peer review is to identify the most excellent and pro- mising research projects. However, sociologists of science and STS scholars have shown that peer review tends to promote solid low-risk projects at the expense of more original and innovative projects that often come with higher risk. It has also been shown that the review process is affected by significant measures of chance. Against this background, the aim of this study is to the- orize the notions of academic judgment and agonistic chance and to present and analyze situations in which expert reviewers are faced with the challenge of trying to decide which grant proposals to select when there is strong dis- agreement. The empirical analysis is based on ethnographic observations of ten panel groups at the Swedish Research Council in the areas of natural and engineering sciences. By focusing on disagreement, the study provides a more in-depth understanding of how agonistic chance creeps into the peer-review process and becomes part of the consensus that is created.

From a purely epistemological point of view, evaluating and predicting the future success of new research projects is often considered very difficult. Is it possible to forecast important findings and breakthrough in science, and if not, then what is the point trying to do it anyway? Still, that is what funding agencies all over the world expect their reviewers to do, but a number of previous studies has shown that this form of evaluation of innovation, promise and future impact are a fundamentally uncertain and arbitrary practice. This is the context that I will discuss in the present essay, and I will claim that there is a deeply irrational element embedded in today's heavy reliance on experts to screen, rank and select among the increasing numbers of good research projects, because they can, in principal, never discern the true potential behind the written proposals. Hence, I think it is motivated to see grant peer review as an 'oracle of science'. My overall focus will be on the limits of competitive funding and also that the writing and reviewing of proposals is a waste of researchers' precious time. And I will propose that we really need to develop new ways of thinking about how we organize research and distribute opportunities within academia.

Den moderna vetenskapen genomsyras av kollegial bedömning – peer review – som på olika sätt fungerar som en intern granskningsprocedur. När anslag ska fördelas till nya forskningsprojekt spelar denna sakkunnighetsbaserade instans en central roll i att generera kollektiviserade beslut. Bedömningen av forskningsansökningars kvalitet har dock visat sig innehålla ett ganska stort mått av tvetydigheter och slump som på ett ofrånkomligt sätt inverkar på de beslutsunderlag som skapas. Trots att peer review kretsar kring att de sakkunniga tillsammans eftersträvar konsensus, präglas denna konsensus likväl av stora variationer och oenighet om hur vissa ansökningar ska värderas. Genom att närmare studera hur oenighet kommer till uttryck och hanteras inom olika beredningsgrupper är det emellertid möjligt att få en fördjupad förståelse för den subtila relationen mellan slump och konsensus i peer review processen.

Följande studie baseras på observationer gjorda på tio av Vetenskapsrådets beredningsgrupper inom natur- och teknikvetenskaper. Den metodologiska utgångspunkten som valts består i att illustrera ett antal fall av oenighet, för att därigenom belysa skillnaderna i hur man kom fram till en praktisk lösning. En problematik som särskilt kommer beröras har att göra med det faktum att oenighet påfallande ofta leder till att bedömarna slår ut varandras favoritansökningar. Detta tar i sin tur på den mer övergripande frågan om hur den enskildes expertkänsla i vissa situationer ställs i direkt motsättning till gruppens samlade expertis, något som kanske inte alltid medför de mest tillfredställande besluten i termer av innovation och risk.

Peer review is integral to the award of funds for academic research. However, as an increasingly large number of researchers attempt to secure limited funding, it is clear that much funding is awarded based on marginal assessments of the quality of different proposals. In this post, Lambros Roumbanis argues that randomly awarding research funding via lotteries presents a more rational, efficient and most importantly unbiased means of distributing research funding.