Communal Responsibility for Ameliorating Fraud

The standard theory of fraud affects the dominant theories of how to respond to scientific fraud. It is commonly suggested that attempts to address the prevalence of scientific fraud should aim to reduce alienation from the norms of science and to increase respect for more distinctively scientific norms (e.g., Bright, forthcoming; Nosek et al.

2012, though see Bright 2017 for a note of skepticism). An alternative suggestion is that we can do more to encourage the effective use of checking mechanisms (e.g., Bruner 2013; also discussed in Lee 2013; Romero 2016). Whichever response is preferred—they are not inconsistent—such solutions proceed in a technocratic vein, by assessing the extent to which the causes of fraud can be addressed so as to ensure that there is less of it. We, however, are interested in a more distinctively moral question: who ought to be morally responsible for reducing the prevalence of fraud?

In an ideal world, each individual would work to avoid making fraudulent claims, and each individual would hold others accountable where fraud was detected. Over time, this would become the norm, yielding a fraud-free science. But fraud has not been eliminated, incentives to commit fraud remain in place, and we cannot plausibly assume full compliance with scientific norms. So we must look for non-ideal strategies for ameliorating the problematic effects of fraud, including the spread of falsehoods, the failure of policies based upon false beliefs, the erosion of trust in the scientific literature, and the breakdown of respect for the norms that allow for epistemically successful publications.

Here too, we build on Dang’s three senses of “collective responsibility.” As we noted above, someone is attributable-responsible if they made the pertinent claim or carried out the relevant procedure. We can typically attribute fraudulent claims or procedures to particular scientists.

Doing so can become difficult or impossible in the two cases we have just discussed; but even here, there must be some individual or group who is causally responsible for producing a claim, even if we can’t figure out precisely who is attributable-responsible for it. And this can yield situations where standards of answerability and accountability become difficult to establish. Recall that someone is answerable-responsible for a claim if they are in a position to produce the reasons that would justify it. Answerability for scientific claims (fraudulent or not) is often diffuse, and whole research teams may sometimes be collectively answerable-responsible for scientific claims. Moreover, in the kinds of cases we have discussed above, answerability tends to break down, generating a situation where no one can answer for problematic claims. Perhaps the scientific community as a whole might somehow be answerable for fraudulent claims that arise in such cases, though difficult questions remain as to what this would amount to. Finally, someone is accountable-responsible if they are the proper target of praise or blame for a scientific product, or if they are justly accorded reward or punishment for making claims that are true, erroneous, or fraudulent. Given the highly social nature of science, we contend that the most plausible thing to say is that the community as a whole is accountable for fraud; and to the extent that we are justified in treating individuals as accountable for fraud, this is because this is a plausible way for the community to fulfill its responsibility for preventing and ameliorating the mal-effects of fraud. This is a complex and contentious claim, so it will help to work through it in more detail.

What does it mean to say that the scientific community as a whole is accountable for the amelioration of fraud? On the one hand, the scientific community is unlikely to satisfy any plausible theory of the constraints on agency. As a “community,” it is far too dis-unified, and far too widely distributed, to carry out any sort of coordinated and intentional actions; moreover, even where trends do emerge within this community, they are rarely under the rational control of any individual or collective agent.

So the community, understood as an agent in its own right, is probably not the right place to look in attempts to change the norms and expectations that give rise to fraudulent action. That said, there is another sense in which the scientific community can be held accountable for the emergence and prevalence of fraud. The members of the scientific community are causally responsible, qua members of the scientific community, for the norms that govern attributions of priority within the scientific credit economy. No individual can determine which norms are accepted by the community. And no individual can change problematic norms where they become stable. But when scientists act together as members of the scientific community, they can begin to shift the salience of expectations to act in particular ways. And over time, this can lead to a shift in the way that the scientific community as a whole operates.

Social norms do not float free from the expectations of the individuals in a community. But at the same time, the expectations that the individuals within a community have depend on the patterns of behavior that are observed within interconnected networks of social actors. As members of a norm-governed community, scientists tend to share numerous values, at least in the minimal sense that they each see themselves, and they each see one another, as possessing the standing to demand compliance with scientific norms. And this tends to be true even where expectations regarding norm compliance are not grounded in joint commitments or shared intentions (cf Hedahl and Huebner 2018). As a result, the stability and prevalence of the norms that allow fraud to emerge can be properly attributed to the networks of social actors who constitute the scientific community. Moreover, since the presence of fraud depends on the presence of norms and incentives that are inherent in the network structure of the scientific credit economy, ameliorative strategies will require a shared commitment among the members of that community to transform the content and the salience of the norms governing scientific practice.

So when we claim that the community as a whole is accountable for fraud, what we mean to suggest is that the proper target of praise and blame in the case of fraud is the interconnected network of scientists, who act in accordance with their roles as community members, and who shape the salience of scientific and credit-seeking norms.

Only the community as a whole has the power to bring about the reforms that could increase or decrease the prevalence of fraud in the non-ideal world. There may not be an agent which constitutes the scientific community, but effective anti-fraud action can only happen through change that works upon this diffuse network of interlinked scientists, enforcing norms and constituting credit through their praise and esteem, and thus generating different expectations about risks and reward. But this must occur through the actions of individual scientists, who are working to reshape the credit-seeking economy. According to the theory outlined in section 25.1, scientific fraud tends to arise as a result of the incentive structure that scientists operate within, as well as the efficacy of the social norms that scientists are supposedly subject to. When fraudulent claims are entered into the scientific literature, there is always some individual or identifiable group to whom the claim is properly attributable. But no individual or group that is smaller than the whole community has the power to modify the credit system, or to shape the norms that will increase or decrease the prevalence of fraud in the non-ideal world that we inhabit. As such, we contend that only the community as a whole can see to it that there is less fraud; that the scientific community as a whole must actively work to minimize scientific fraud, and that it collectively should be praised or blamed for arranging itself in ways that yield greater or lesser amounts of fraud.

As to how this responsibility should be discharged, we think the scientific community is broadly on the right track already.

We should bring credit incentives into line with obeying epistemic norms of science, foster respect for those norms, and avoid anomie. As such, educational institutions should do their best to inculcate and encourage a sense of honesty and allegiance to the epistemic norms of science (Du Bois 1898). Initiatives such as encouraging pre-registration to ensure fraudulent research practices do not yield accredited publications ought to be supported (van ‘t Veer and Giner-Sorolla 2016). Moreover, robust uses of checking mechanisms via replication (OSC 2015), and attempts at multi-method triangulation (Munafo and Davey Smith 2018), should be used to ferret out false claims that have already been entered into the literature, making it less likely that scientists will gain lasting priority credit for claims that are false. Together, these practices will help disincentivize fraud. Additionally, mechanisms should be put in place to ensure that taking part in such practices is rewarded in the credit economy. This might involve favored access to funding, rewards, or publication venues for studies of the required form. Finally, where there is evidence of malpractice, ensuring that there are procedures in place for retraction and punishment will further disincentivize fraudulent behavior. This may involve making individuals or groups answer for the instances of fraud they commit. But individual instances of fraud are always embedded in larger social patterns; and the agent that is answerable for regulating these patterns is the scientific community that is constituted by networks of interacting individuals and institutions.

Notes

1 Both BH and LKB made substantial contributions to the writing and revision of this chapter; and both authors approved its submission.

2 While it is not exactly the same phenomenon, the problem of the garden of forking paths (Gelman and Loken 2013) also contributed to the replication crisis by creating situations in psychology where checking mechanisms could not track norm compliance, while the temptation to establish priority and gain credit remained strong.

3 Dang (submitted) is primarily concerned with questions of epistemic responsibility.

But she does note in passing that similar issues are likely to arise in the context of collective moral responsibility. We agree, and we argue in the remainder of this chapter that questions about moral and epistemic responsibility are deeply connected, at least in the context of questions about scientific responsibility. Following Dang, we also suggest that an account of collective moral responsibility in science must begin by acknowledging that these three kinds of responsibility can converge or diverge as a result of the organization of a scientific research group.

4 Drawing on an argument advanced by Lenhard and Winsberg (2010: 256—7), we might see such collaborations as kludged architectures, which display a sort of fuzzy modularity: each research group is organized in accordance with the norms of their local credit economy, so their data and inferences are shaped by a mixture of principled science and locally salient practices of credit-seeking; and the interactions between these groups shape the content of the information that is propagated through such collaboration, as data are continuously exchanged between research groups, and as queries are made for more data or further interpretations.

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Source: Bazargan-Forward Saba, Tollefsen Deborah (eds.). The Routledge Handbook of Collective Responsibility. Routledge,2020. — 538 p.. 2020

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