Attribution Of Credit Research Articles

Team up with AI or Human? Investigating Candidates’ Self-Categorization as Fluidity and Ingroup-Serving Attribution When Judged by a Human–AI Hybrid Jury

As artificial intelligence (AI) judges are increasingly pervasive in decision-making, it is important to investigate candidates’ reactions to decisions made by human–AI hybrid juries. This study investigates candidates’ attribution of credit for success and blame for failure to the three agents in question: a human judge, an algorithmic judge, and the candidate oneself. An experiment with 3 (jury type: human-dominated, algorithm-dominated, vs. equally dominated) × 2 (decision outcome: positive vs. negative) between-subjects factorial design was conducted, with 346 valid responses. Our findings demonstrate a partial ingroup-serving attribution dependent on the outcome favorability and a significant effect of relative power status within the human–AI hybrid jury on grouping and attribution. This study reflects the fluidity of identity and self-categorization of human users when facing AI and other humans. We propose that people take a utility-oriented glance at AI in multi-agent decision-making situations.

Perceived government-expert discord and evaluation of COVID-19 policies in Hong Kong

ABSTRACT This study examines citizens’ retrospective evaluation of government policies during the COVID-19 pandemic. It focuses specifically on the impact of perceived government – expert discord, i.e. public perceptions of disagreement between government officials and the medical expert community. Medical experts played important roles during the pandemic and enjoyed high levels of credibility, whereas government leaders were sometimes seen as driven by political motivations. Hence, perceived government – expert discord might negatively affect policy evaluation. Analysis of a post-pandemic survey in Hong Kong (N = 1,002) shows that people who perceive significant government – expert discord are likelier to blame the government for negative happenings during the pandemic, less likely to credit the government for positive outcomes, and less likely to see the government’s control measures as appropriate. These relationships are stronger among people who suffered more, economically or mentally, during the pandemic. Credit attribution, blame attribution, and perceived appropriateness of control measures, in turn, influence overall policy evaluation.

To Authenticity, and Beyond! Building Safe and Fair Generative AI Upon the Three Pillars of Provenance.

Provenance facts, such as who made an image and how, can provide valuable context for users to make trust decisions about visual content. Against a backdrop of inexorable progress in generative AI for computer graphics, over two billion people will vote in public elections this year. Emerging standards and provenance enhancing tools promise to play an important role in fighting fake news and the spread of misinformation. In this article, we contrast three provenance enhancing technologies-metadata, fingerprinting, and watermarking-and discuss how we can build upon the complementary strengths of these three pillars to provide robust trust signals to support stories told by real and generative images. Beyond authenticity, we describe how provenance can also underpin new models for value creation in the age of generative AI. In doing so, we address other risks arising with generative AI such as ensuring training consent, and the proper attribution of credit to creatives who contribute their work to train generative models. We show that provenance may be combined with distributed ledger technology to develop novel solutions for recognizing and rewarding creative endeavor in the age of generative AI.

Group authorship, an excellent opportunity laced with ethical, legal and technical challenges

ABSTRACT Group authorship (also known as corporate authorship, team authorship, consortium authorship) refers to attribution practices that use the name of a collective (be it team, group, project, corporation, or consortium) in the authorship byline. Data shows that group authorships are on the rise but thus far, in scholarly discussions about authorship, they have not gained much specific attention. Group authorship can minimize tensions within the group about authorship order and the criteria used for inclusion/exclusion of individual authors. However, current use of group authorships has drawbacks, such as ethical challenges associated with the attribution of credit and responsibilities, legal challenges regarding how copyrights are handled, and technical challenges related to the lack of persistent identifiers (PIDs), such as ORCID, for groups. We offer two recommendations: 1) Journals should develop and share context-specific and unambiguous guidelines for group authorship, for which they can use the four baseline requirements offered in this paper; 2) Using persistent identifiers for groups and consistent reporting of members’ contributions should be facilitated through devising PIDs for groups and linking these to the ORCIDs of their individual contributors and the Digital Object Identifier (DOI) of the published item.

Intuitive credit attribution and the priority rule

ABSTRACT When a good idea is discovered, who gets credit for it? This is an important question in science, the arts, law, and everyday life. We suggest that people have intuitions about credit ownership that depend on three factors: (i) whether the idea suggests the discoverer is competent; (ii) whether the discovery elicits gratitude toward the discoverer; (iii) who the first individual to come up with the idea is. We test these intuitions in three vignette experiments with UK participants, in the context of priority disputes in science. In Experiment 1, participants find a discoverer less competent and award less credit to them for a scientific idea if they perceive that the discoverer could have plagiarized another discoverer, but attributions of credit are also shown to differ from attributions of competence. In Experiment 2, participants are more grateful toward, and award more credit to a discoverer who makes their discovery public. In Experiment 3, participants are more biased toward the first discoverer in terms of credit attribution than in terms of competence attribution or feelings of gratitude. In conclusion, we suggest that intuitions of credit ownership help explain the popularity and endurance of the priority rule in science, by which all the credit of a discovery is supposed to go to the first discoverer.

“RISE AND FALL” OF THE WALRASIAN PROGRAM IN ECONOMICS: A SOCIAL AND INTELLECTUAL DYNAMICS OF THE GENERAL EQUILIBRIUM THEORY

This paper aims at understanding social practices and institutions that ensured the transnational diffusion, recognition, and renewal of the research program in the General Equilibrium Theory (GET), in spite of multiple critics and apparent theoretical dead ends. First, we trace the main conceptual developments of the Walrasian GET program since the 1950s and thus elaborate on its intellectual identity. Then, based on a systematic study of the educational and professional trajectories typical for several generations of GET scholars, we analyze a social form taken by this transnational and multidisciplinary “scientific community”: an institutional dynamics of the Walrasian GET program, most common career patterns, and the forms of international and intergenerational transmission. We construct a database of GET theorists and apply to this dataset a technique of Multiple Correspondence Analysis (MCA) in order to investigate the relational patterns between attribution of scientific credit (symbolic capital) and biographical properties in a transnational space of the GET scholars.

Who Made This? Algorithms and Authorship Credit.

Producers and creators often receive assistance with work from other people. Increasingly, algorithms can provide similar assistance. When algorithms assist or augment producers, does this change individuals' willingness to assign credit to those producers? Across four studies spanning several domains (e.g., painting, construction, sports analytics, and entrepreneurship), we find evidence that producers receive more credit for work when they are assisted by algorithms, compared with humans. We also find that individuals assume algorithmic assistance requires more producer oversight than human assistance does, a mechanism that explains these higher attributions of credit (Studies 1-3). The greater credit individuals assign to producers assisted by algorithms (vs. other people) also manifests itself in increased support for those producers' entrepreneurial endeavors (Study 4). As algorithms proliferate, norms of credit and authorship are likely changing, precipitating a variety of economic and social consequences.

Semantic similarity-based credit attribution on citation paths: a method for allocating residual citation to and investigating depth of influence of scientific communications

Semantic similarity-based credit attribution on citation paths: a method for allocating residual citation to and investigating depth of influence of scientific communications

The quality of the web of science data: a longitudinal study on the completeness of authors-addresses links

The author-affiliation links are the essential elements used for multiple purposes, such as the disambiguation of authors, the attribution of credits of a publication and fractional counting, the analysis of scientific networks, etc. In this article we analyzed the author-affiliation link quality in the Web of Science (WoS) database between 2000 and 2021. We analyzed the link completeness for 32,676,914 scientific publications under different angles: WoS index, document type and the number of authors per publication. The analysis showed that the author-affiliation link begins to be well informed from 2008. The share of publications for which all addresses and all authors are linked is close to 100% from 2016. The results show a strong variability according to the WoS index, the document type and the number of authors per publication. AHCI is the index with the highest completeness rate, unlike the SCI. For the document type, these are the Conference proceedings where the completeness rate is better and/or can be completed. Regarding the number of authors, statistics show that the higher the number, the more addresses and unlinked authors there are finally, the analysis of a random sample of 100 publications showed that in more than 50% of the cases, the author-address links do not exist in the original publication, and the WoS reproduced only the available information provided by the editor.

Evolution and adoption of contributor role ontologies and taxonomies

AbstractContributor Role Ontologies and Taxonomies (CROTs) are standard vocabularies to describe individual contributions to a scholarly project or research output. Contributor Roles Taxonomy (CRediT) is one of the most widely used CROTs, and has been adopted by numerous journals to describe author's contributions, and recently formalized as a ANSI/NISO standard. Despite these developments, there is still much work left to be done to improve how CROTs are used across different research domains, research output types, and scholarly workflows. In this paper, we describe how CROTs could be extended to include roles from various disciplines in an ethical and inclusive manner. We explore potential approaches to apply CROTs to diverse research objects and various disciplines; as well as envision their integration into various scholarly workflows, such as promotion and tenure in academic institutions. Lastly, we discuss potential mechanisms for wide adoption and use. While acknowledging that improving current systems of attribution is a slow and iterative process, we believe that engaging the community in the evolution of CROTs will ultimately enhance the ethical attribution of credit and responsibilities in scholarly publications.

Who Moved my Welfare Scheme? Federalism and the Politics of Credit Attribution in Rural India

The growing popularity of welfare schemes across several developing countries is crucially predicated on whether incumbent governments can derive consequent electoral benefits. A federal structure like India’s, characterized by overlapping policy design and implementation responsibilities, provides opportunities for diffused credit attribution. Therefore, the question of electoral returns depends on the ability of voters to assign credit for welfare benefits to different levels of government. We investigate voter attribution of credit for welfare policies and their electoral consequences using data from a large sample survey from the 2014 parliamentary elections in India. Our results indicate that welfare delivery and credit attribution mattered to the electorate and was one of the few factors that worked in favour of the incumbent United Progressive Alliance, but it was not decisive enough to yield an overall electoral victory. There are strong political imperatives for the roll-out and expansion of welfare schemes, as well as contestations around credit claims. Our analysis provides empirical support for intense party competition over credit for welfare benefits in a federal structure—which has been widely observed and commented upon in the media but has not been econometrically tested for its electoral significance. We find that welfare schemes are an essential dimension of performance evaluation by the electorate, a problem understudied in the extant literature on ‘performance voting’ and undertheorized in the literature on ‘distributive politics’ and ‘welfare provisions’, particularly in a federal structure.

Women are credited less in science than men

There is a well-documented gap between the observed number of works produced by women and by men in science, with clear consequences for the retention and promotion of women1. The gap might be a result of productivity differences2–5, or it might be owing to women’s contributions not being acknowledged6,7. Here we find that at least part of this gap is the result of unacknowledged contributions: women in research teams are significantly less likely than men to be credited with authorship. The findings are consistent across three very different sources of data. Analysis of the first source—large-scale administrative data on research teams, team scientific output and attribution of credit—show that women are significantly less likely to be named on a given article or patent produced by their team relative to their male peers. The gender gap in attribution is present across most scientific fields and almost all career stages. The second source—an extensive survey of authors—similarly shows that women’s scientific contributions are systematically less likely to be recognized. The third source—qualitative responses—suggests that the reason that women are less likely to be credited is because their work is often not known, is not appreciated or is ignored. At least some of the observed gender gap in scientific output may be owing not to differences in scientific contribution, but rather to differences in attribution.

Stage 2 Registered Report: How responsibility attributions to self and others relate to outcome ownership in group decisions.

Background: Responsibility judgements have important consequences in human society. Previous research focused on how someone's responsibility determines the outcome they deserve, for example, whether they are rewarded or punished. Here, in a pre-registered study (Stage 1 Registered Report: https://doi.org/10.12688/wellcomeopenres.16480.2), we investigate the opposite link: How outcome ownership influences responsibility attributions in a social context. Methods: In an online study, participants in a group of three perform a majority vote decision-making task between gambles that can lead to a reward or no reward.Only one group member receives the outcome and participants evaluate their and the other players' responsibility for the obtained outcome. Results: We found that outcome ownership increases responsibility attributions even when the control over an outcome is similar.Moreover, ownership had an effect on the valence bias: participants' higher responsibility attributions for positive vs negative outcomes was stronger for players who received the outcome. Finally, this effect was more pronounced when people rated their own responsibility as compared to when they were rating another's player responsibility. Conclusions: The findings of this study reveal how credit attributions can be biased toward particular individuals who receive outcomes as a result of collective work, both when people judge their own and someone else's responsibility.

Stage 2 Registered Report: How responsibility attributions to self and others relate to outcome ownership in group decisions

Background: Responsibility judgements have important consequences in human society. Previous research focused on how someone's responsibility determines the outcome they deserve, for example, whether they are rewarded or punished. Here, in a pre-registered study (Stage 1 Registered Report: https://doi.org/10.12688/wellcomeopenres.16480.2), we investigate the opposite link: How outcome ownership influences responsibility attributions in a social context. Methods: In an online study, participants in a group of three perform a majority vote decision-making task between gambles that can lead to a reward or no reward. Only one group member receives the outcome and participants evaluate their and the other players' responsibility for the obtained outcome. Results: We found that outcome ownership increases responsibility attributions even when the control over an outcome is similar. Moreover, ownership had an effect on the valence bias: participants’ higher responsibility attributions for positive vs negative outcomes was stronger for players who received the outcome. Finally, this effect was more pronounced when people rated their own responsibility as compared to when they were rating another’s player responsibility. Conclusions: The findings of this study reveal how credit attributions can be biased toward particular individuals who receive outcomes as a result of collective work, both when people judge their own and someone else’s responsibility.

The vexing but persistent problem of authorship misconduct in research

This paper examines authorship misconduct: practices such as gift, guest, honorary and ghost authorship (excluding plagiarism) that involve inappropriate attribution of authorship credits. Drawing on the existing literature, we describe the extent of authorship misconduct and why it presents a problem. We then construct a simple matching model of guest authorship to show how researchers can form teams (of two) where one researcher free-rides off the efforts of the other; at equilibrium, the latter is content for this free-riding to occur, rather than forming a different team involving no free-riding. We discuss how this model can be generalized to incorporate honorary and gift authorship, and why capturing ghost authorship may require significant changes to the modelling. While formal (game-theoretic) modelling of other aspects of research misconduct is prevalent in the literature, to our knowledge, ours is the first attempt to isolate the strategic interaction that leads to authorship misconduct. If authorship misconduct is a rational choice by researchers, we investigate the use of a monitoring-punishment approach to eliminate the free-riding equilibria. The possibility of monitoring is not just theoretical: we outline the recent advances in distributed ledger technology and authorship forensics that make monitoring of research workflows a viable strategy for institutions to curb authorship misconduct. One of the advantages of working with our simple model is that it provides a framework to examine the relationship between efficiency and ethics in this context, an issue that has by and large been ignored in the literature.

Stage 2 Registered Report: How responsibility attributions to self and others relate to outcome ownership in group decisions.

Background: Responsibility judgements have important consequences in human society. Previous research focused on how someone's responsibility determines the outcome they deserve, for example, whether they are rewarded or punished. Here, in a pre-registered study (Stage 1 Registered Report: https://doi.org/10.12688/wellcomeopenres.16480.2), we investigate the opposite link: How outcome ownership influences responsibility attributions in a social context. Methods: In an online study, participants in a group of three perform a majority vote decision-making task between gambles that can lead to a reward or no reward.Only one group member receives the outcome and participants evaluate their and the other players' responsibility for the obtained outcome. Results: We found that outcome ownership increases responsibility attributions even when the control over an outcome is similar.Moreover, ownership had an effect on the valence bias: participants' higher responsibility attributions for positive vs negative outcomes was stronger for players who received the outcome. Finally, this effect was more pronounced when people rated their own responsibility as compared to when they were rating another's player responsibility. Conclusions: The findings of this study reveal how credit attributions can be biased toward particular individuals who receive outcomes as a result of collective work, both when people judge their own and someone else's responsibility.

The gendered nature of authorship.

Authorship is the primary form of symbolic capital in science. Despite this, authorship is rife with injustice and malpractice, with women expressing concerns regarding the fair attribution of credit. Based on an international survey, we examine gendered practices in authorship communication, disagreement, and fairness. Our results demonstrate that women were more likely to experience authorship disagreements and experience them more often. Their contributions to research papers were more often devalued by both men and women. Women were more likely to discuss authorship with coauthors at the beginning of the project, whereas men were more likely to determine authorship unilaterally at the end. Women perceived that they received less credit than deserved, while men reported the opposite. This devaluation of women’s work in science creates cumulative disadvantages in scientific careers. Open discussion regarding power dynamics related to gender is necessary to develop more equitable distribution of credit for scientific labor.

Priority and privilege in scientific discovery

The priority rule in science has been interpreted as a behavior regulator for the scientific community, which benefits society by adequately structuring the distribution of intellectual labor across pre-existing research programs. Further, it has been lauded as an intuitively fair way to reward scientists for their contributions, as a special case of society’s “grand reward scheme”. However, we will argue that the current formal framework utilized to model the priority rule idealizes away important aspects of credit attribution, and does so in a way that impacts the conclusions drawn regarding its function in scientific communities. In particular, we consider the social dynamics of credit attribution in order to show that the priority rule can foster structural disadvantages in socially diverse science, as well as drive the distribution of intellectual labor away from optimal.

Developer Credit: Para-Industrial Hierarchies of In-Game Credit Attribution in the Video Game Industry

Developer credit has been a contested issue in the video game industry since the 1970–80s, when Atari prevented its programmers from publicly claiming authorship for games they had developed. The negotiations over what constitutes a noteworthy contribution to video game development are ongoing and play out in the unregulated space of in-game credits. Here, some creators get top billing akin to film and television credits, while others struggle to be recognized for their work. By analyzing in-game credits of 100 contemporary games published between 2016 and 2020 and representing four major sectors of video game production (AAA, AA, indie, and freemium games as service), I identify recurrent patterns, such as opening credits, order, role descriptions (or lack thereof), and systematic credit omission, that both reinforce and subvert the notion of core development roles and above-the-line/below-the-line divisions.

Stage 1 Registered Report: How responsibility attributions to self and others relate to outcome ownership in group decisions.

Responsibility judgements have important consequences in human society. Previous research focused on how someone's responsibility determines the outcome they deserve, for example, whether they are rewarded or punished. Here, we investigate the opposite link: How outcome ownership influences responsibility attributions in a social context.Participants in a group of three perform a majority vote decision-making task between gambles that can lead to a reward or no reward.Only one group member receives the outcome and participants evaluate their and the other players' responsibility for the obtained outcome. Two hypotheses are tested: 1) Whether outcome ownership increases responsibility attributions even when the control over an outcome is similar.2) Whether people's tendency to attribute higher responsibility for positive vs negative outcomes will be stronger for players who received the outcome. The findings of this study may help reveal how credit attributions can be biased toward particular individuals who receive outcomes as a result of collective work.