1,720,963 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Limits of the numerical: the abuses and uses of quantification, ed. C. Newfield, A. Alexandrova and S. John. University of Chicago Press, 2022, 317 pages.
No full textAI and bureaucratic discretion
No full textAlgorithmic decision-making has the potential to radically reshape policy-making and policy implementation. Many of the moral examinations of AI in government take AI to be a neutral epistemic tool or the value-driven analogue of a policymaker. In this paper, I argue that AI systems in public administration are often better analogised to a street-level bureaucrat. Doing so opens up a host of questions about the moral dispositions of such AI systems. I argue that AI systems in public administration often act as indifferent bureaucrats, and that this can introduce a problematic homogeneity in the moral dispositions in administrative agencies
Fairness
No full textDespite widespread agreement that algorithmic bias is a problem, there is a lack of agreement about what to do about it. This chapter argues that what should be done about algorithmic bias depends on whether the problem of algorithmic bias is conceptualized as a problem of fairness, or some other problem of justice. It substantiates this claim by examining the debate over different formal fairness metrics. One compelling metric for measuring whether a system is fair measures whether the system is calibrated, or whether a prediction has equal evidential value regardless of an individual’s group membership. Calibration exemplifies a compelling notion of accuracy, and of fairness, in treating like cases alike. However, there can be a tradeoff between making systems fair, in this sense, and making them more just: to make more accurate predictions, a system may use social patterns that reinforce structures of unjust disadvantage. In response to this tradeoff, the chapter argues that in situations of injustice, other values of justice ought to be privileged over fairness, as fairness has no value in the absence of just background institutions. It concludes by drawing out five proposals for better governance of AI for justice and fairness from the philosophical discussion of fairness and justice in AI. These are a values-first approach to bias interventions, de-coupling decision processes, explicitly modeling structural injustice, interventions to increase data quality, and the use of (weighted) lotteries rather than decision thresholds
AI survival stories, types of risk, and the precautionary principle
No full textCappelen, Goldstein, and Hawthorne’s article offers a refreshing new perspective on questions of AI safety. Debates over AI and existential risk standardly start from a background assumption of humanity’s continued survival, and then reason about the probability of catastrophic outcomes. This paper, by contrast, flips that mode of reasoning on its head: a decision-maker should start from the assumption that powerful AI systems will destroy humanity, and then reason about the different outcomes in which humanity is saved from such an existential threat. Doing so enables us to better partition the space of possible events in which saving occurs, and so to come to more justified probabilities of humanity being saved. The article also illustrates the value of this approach by defending particular claims about promising paths to avert existential risk. To do so, it puts forth a model that different parties to the debate can use to calculate the probability that humanity is destroyed. The authors also defend a number of claims about the most likely mechanisms for realizing each of the four survival stories.
Freedom at work: understanding, alienation, and the AI-driven workplace
No full textThis paper explores a neglected normative dimension of algorithmic opacity in the workplace and the labor market. It argues that explanations of algorithms and algorithmic decisions are of noninstrumental value. That is because explanations of the structure and function of parts of the social world form the basis for reflective clarification of our practical orientation toward the institutions that play a central role in our life. Using this account of the noninstrumental value of explanations, the paper diagnoses distinctive normative defects in the workplace and economic institutions which a reliance on AI can encourage, and which lead to alienation
Fairness and randomness in decision-making: the case of decision thresholds
No full textThis paper defends the role of lotteries in fair decision-making. It does so by targeting the use of decision thresholds to convert algorithmic predictions and classifications into decisions. Using an account of fairness from John Broome, the paper argues that decision thresholds are sometimes unfair, and that lotteries would be a fairer allocation method. It closes by dealing with two objections. First, it deals with the objection that lotteries should only be used to break ties in cases where individuals’ claims are equally strong. Here, the paper gives a new argument for Broome’s view, targeting decision criteria that are arbitrary and highly standardized. It then defends the arguments of the paper against the objection that lotteries are not morally superior to other methods of arbitrary choosing
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