David Teira

In actuarial parlance, the price of an insurance policy is considered fair if customers bearing the same risk are charged the same price. The estimate of this fair amount hinges on the expected value obtained by weighting the different claims by their probability. We argue that, historically, this concept of actuarial fairness originates in an Aristotelian principle of justice in exchange (equality in risk). We will examine how this principle was formalized in the 16th century and shaped in life insurance during the following two hundred years, in two different interpretations. The Domatian account of actuarial fairness relied on subjective uncertainty: An agreement on risk was fair if both parties were equally ignorant about the chances of an uncertain event. The objectivist version grounded any agreement on an objective risk estimate drawn from a mortality table. We will show how the objectivist approach collapsed in the market for life annuities during the 18th century, leaving open the question of why we still speak of actuarial fairness as if it were an objective expected value.

In this paper I offer an account of the normative dimension implicit in D. Bernoulli’s expected utility functions by means of an analysis of the juridical metaphors upon which the concept of mathematical expectation was moulded. Following a suggestion by the late E. Coumet, I show how this concept incorporated a certain standard of justice which was put in question by the St. Petersburg paradox. I contend that Bernoulli would have solved it by introducing an alternative normative criterion rather than a positive model of decision making processes

In this paper I study how the theoretical categories of consumption theory were used by Milton Friedman in order to classify empirical data and obtain predictions. Friedman advocated a case by case definition of these categories that traded theoretical coherence for empirical content. I contend that this methodological strategy puts a clear incentive to contest any prediction contrary to our interest: it can always be argued that these predictions rest on a wrong classification of data. My conjecture is that this methodological strategy can contribute to explain why Friedman’s predictions never generated the consensus he expected among his peers.

Our goal in this paper is to articulate a precise concept of at least a certain kind of disease-mongering, showing how pharmaceutical marketing can commercially exploit certain diseases when their best definition is given through the success of a treatment in a clinical trial. We distinguish two types of disease-mongering according to the way they exploit the definition of the trial population for marketing purposes. We argue that behind these two forms of disease-mongering there are two well-known problems in the statistical methodology of clinical trials (the reference class problem and the distinction between statistical and clinical significance). Overcoming them is far from simple

Pharmaceutical paternalism is the normative stance upheld by pharmaceutical regulatory agencies like the US Food and Drug Administration. These agencies prevent patients from accessing treatments declared safe and ineffective for the patient’s good without their consent. Libertarian critics of the FDA have shown a number of significant flaws in regulatory paternalism. Against these objections, I will argue that, in order to make an informed decision about treatments, a libertarian patient should request full disclosure of the uncertainty about an experimental treatment. But pharmaceutical markets, on their own, are not a reliable source of information about such uncertainty. And companies have the power to capture any independent expert who may assess it. Therefore, the libertarian is better off deferring on an independent regulatory body the assessment of the pharmaceutical risks, constraining access to treatments until tested.

Debiasing procedures are experimental methods aimed at correcting errors arising from the cognitive biases of the experimenter. We discuss two of these methods, the predesignation rule and randomization, showing to what extent they are open to the experimenter’s regress: there is no metarule to prove that, after implementing the procedure, the experimental data are actually free from biases. We claim that, from a contractarian perspective, these procedures are nonetheless defensible since they provide a warrant of the impartiality of the experiment: we only need proof that the result has not been intentionally manipulated for prima facie acceptance

In this article we explore an argumentative pattern that provides a normative justification for expected utility functions grounded on empirical evidence, showing how it worked in three different episodes of their development. The argument claims that we should prudentially maximize our expected utility since this is the criterion effectively applied by those who are considered wisest in making risky choices (be it gamblers or businessmen). Yet, to justify the adoption of this rule, it should be proven that this is empirically true: i.e. that a given function allows us to predict the choices of that particular class of agents. We show how expected utility functions were introduced and contested in accordance with this pattern in the 18th century and how it recurred in the 1950s when Allais made his case against the neo-Bernoullians

This paper discusses the so-called non-interference assumption (NIA) grounding causal inference in trials in both medicine and the social sciences. It states that for each participant in the experiment, the value of the potential outcome depends only upon whether she or he gets the treatment. Drawing on methodological discussion in clinical trials and laboratory experiments in economics, I defend the necessity of partial forms of blinding as a warrant of the NIA, to control the participants’ expectations and their strategic interactions with the experimenter

La renta básica se nos presenta en la obra de Philippe van Parijs como una propuesta política filosóficamente argumentada, de modo tal que convencerá tanto al teórico de la justicia como al ciudadano que votará su implantación. En este artículo analizamos la argumentación de van Parijs mostrando cómo la efectividad política de sus tesis sólo se sostiene a costa de reducir el debate sobre la renta básica a los términos de su propia concepción de la ética. Ponemos en duda, por nuestra parte, el alcance de esta reducción sobre un doble plano: diluye por completo la dimensión prudencial de toda argumentación política, y no deja más alternativa que la educación sentimental para quienes no se dejen convencer por el equilibrio reflexivo

Over the last decade, philosophers of science have extensively criticized the epistemic superiority of randomized controlled trials for testing safety and effectiveness of new drugs, defending instead various forms of evidential pluralism. We argue that scientific methods in regulatory decision-making cannot be assessed in epistemic terms only: there are costs involved. Drawing on the legal distinction between rules and standards, we show that drug regulation based on evidential pluralism has much higher costs than our current RCT-based system. We analyze these costs and advocate for evaluating any scheme for drug regulatory tests in terms of concrete empirical benchmarks, like the error rates of regulatory decisions.

We discuss the role of practical costs in the epistemic justification of a novice choosing expert advice, taking as a case study the choice of an expert statistician by a lay politician. First, we refine Goldman’s criteria for the assessment of this choice, showing how the costs of not being impartial impinge on the epistemic justification of the different actors involved in the choice. Then, drawing on two case studies, we discuss in which institutional setting the costs of partiality can play an epistemic role. This way we intend to show how the sociological explanation of the choice of experts can incorporate its epistemic justification.

In this paper I explore a positivist methodological tradition in early demand theory, as exemplified by several common traits that I draw from the works of V. Pareto, H. L. Moore and H. Schultz. Assuming a current approach to explanation in the social sciences, I will discuss the building of their various explanans, showing that the three authors agreed on two distinctive methodological features: the exclusion of any causal commitment to psychology when explaining individual choice and the mandate to test the truth of demand theory on aggregate data by statistical means. However, I also contend, from an epistemological point of view, that the truth of demand theory was conceived of in three different ways by our authors. Inspired by Poincaré, Pareto assumed that many different theories could account for the same data on individual choice, coming close to a kind of conventionalism -though I prefer to refer to this position as theoreticism. Moore was himself akin to Pearson's approach, which could be named descriptivist insofar as it resolved scientific laws into statistical descriptions of the data. Finally, Schultz tried to reconcile both approaches in an adequationist stance with no success, as we shall see.

Why scientists reach an agreement on new experimental methods when there are conflicts of interest about the evidence they yield? I argue that debiasing methods play a crucial role in this consensus, providing a warrant about the impartiality of the outcome regarding the preferences of different parties involved in the experiment. From a contractarian perspective, I contend that an epistemic pre-requisite for scientists to agree on an experimental method is that this latter is neutral regarding their competing interests. I present two medical experiments (on smallpox inoculation and Mesmerism) in which debiasing procedures such as blinding and data tabulation provided warrants of impartiality that made people agree on the experimental design even if they disagreed on the outcome.

One of the defining features of the classical gene was its position. In molecular genetics, positions are defined instead as nucleotide numbers and there is no clear correspondence with its classical counterpart. However, the classical gene position did not simply disappear with the development of the molecular approach, but survived in the lab associated to different genetic practices. The survival of classical gene position would illustrate Waters’ view about the practical persistence of the genetic approach beyond reductionism and anti-reductionist claims. We show instead that at the level of laboratory practices there are also reductive processes, operating through the rise and fall of different techniques. Molecular markers made the concept of classical gene position practically dispensable, leading us to rethink whether it had any causal role or was just a mere heuristic.

Did the impartiality of clinical trials play any role in their acceptance as regulatory standards for the safety and efficacy of drugs? According to the standard account of early British trials in the 1930s and 1940s, their impartiality was just rhetorical: the public demanded fair tests and statistical devices such as randomization created an appearance of neutrality. In fact, the design of the experiment was difficult to understand and the British authorities took advantage of it to promote their own particular interests. I claim that this account is based on a poorly defined concept of experimental fairness . I present an alternative approach in which a test would be impartial if it incorporates warrants of non-manipulability. With this concept, I reconstruct the history of British trials showing that they were indeed fair and this fairness played a role in their acceptance as regulatory yardsticks

I want to expand the pragmatist view of probability advocated by Roberto Torretti, drawing on the propensity approach. In the first part, I will show how the concept of mathematical expectation originally formalized an Aristotelian principle of justice. In the second half, I will present the game-theoretic approach to probability developed by Shafer and Vovk, showing how it allows us to interpret the original normativity of mathematical expectations. I will finally discuss how this latter view contributes to a pragmatist understanding of probability, as Torretti advocates, although with broader foundations than the physical symmetries of standard propensities.

Political fact-checkers evaluate the truthfulness of politicians’ claims. This paper contributes to an emerging scholarly debate on whether fact-checkers treat political parties differently in a systematic manner depending on their ideology (bias). We first examine the available approaches to analyze bias and then present a new approach in two steps. First, we propose a logistic regression model to analyze the outcomes of fact-checks and calculate how likely each political party will obtain a truth score. We test our model with a sample of fact-checks from Newtral, a major Spanish fact-checker. Our model would signal bias under two assumptions: a) all political parties are on average equally accurate in their statements; b) the verification method gives precise instructions and is implemented systematically. We investigate this second assumption with a series of interviews with Newtral fact-checkers. We show that standard verification protocols are so loosely implemented that fact-checks reflect a set of journalistic decisions, rather than a bias in the statistical sense. We call for a more rigorous definition of verification methods as a pre-requisite for an unbiased assessment of politician’s claims.

I analyze cultural relativism as a methodological strategy to correct for ethnocentric biases in anthropological fieldwork. I discuss the format debiasing norms may adopt depending on whether a discipline has a causal or interpretative outlook. Franz Boas and his school advocated for an interpretative approach to ethnographic fieldwork, in which cultural relativism was implemented as a standard to be interpreted by expert third parties. Legitimate as it may be as a debiasing method, it does not allow anthropologists to adjudicate their debates on biases in their ethnographic record.

In this paper, Isuggest that placebo effects, as we know them today, should be understood as experimental phenomena, low-level regularities whose causal structure is grasped through particular experimental designs with little theoretical guidance. Focusing on placebo interventions with needles for pain reduction -one of the few placebo regularities that seems to arise in meta-analytical studies- I discuss the extent to which it is possible to decompose the different factors at play through more fine-grained randomized clinical trials. My sceptical argument is twofold. On the one hand, I argue that experiments alone are not enough to standardize interventions, and that it is necessary to include theories. On the other hand, I argue that the social interactions that seem to be part of placebo effects are difficult, if not impossible, to blind. Therefore, the measurement biases arising from the participants’ reactivity to the experimental setup cannot be controlled for. Further decomposition of placebo effects requires a theoretical account of the existing experimental regularities that may guide further tests

I will open the first part of this paper by trying to elucidate the frequentist foundations of RCTs. I will then present a number of methodological objections against the viability of these inferential principles in the conduct of actual clinical trials. In the following section, I will explore the main ethical issues in frequentist trials, namely those related to randomisation and the use of stopping rules. In the final section of the first part, I will analyse why RCTs were accepted for regulatory purposes. I contend that their main virtue, from a regulatory viewpoint, is their impartiality, which is grounded in randomisation and fixed rules for the interpretation of the experiment. Thus the question will be whether Bayesian trials can match or exceed the achievements of frequentist RCTs in all these respects. In the second part of the paper, I will first present a quick glimpse of the introduction of Bayesianism in the field of medical experiments, followed by a summary presentation of the basic tenets of a Bayesian trial. The point here is to show that there is no such thing as “a” Bayesian trial. Bayesianism can ground many different approaches to medical experiments and we should assess their respective virtues separately. Thus I present two actual trials, planned with different goals in mind, and assess their respective epistemic, ethical and regulatory merits. In a tentative conclusion, I contend that, given the constraints imposed by our current regulatory framework, impartiality should preside over the design of clinical trials, even at the expense of many of their inferential and ethical virtues.

Publishers are signing transformative agreements with different research institutions and funding bodies across the world. These agreements establish that the institution or funder makes a block payment in exchange for an annual quota of OA papers allowing their affiliated authors to publish OA in an agreed list of journals, at no extra cost to the individual author. This is a step towards the transformation of these journals into a Gold (commercial) Open Access regime. In January 2023, the members of the OA working group contacted the editors of the 27 journals listed as relevant for the field of philosophy of science on the website of the Philosophy of Science Association. We asked the editors-in-chief two questions: 1) Did your publishers discuss any plans to transition to gold open access exclusively with you? If so, how would it work? 2) If the publishers did contact you regarding this matter, what is your view on the project? We collected 22 answers. The executive summary is: 10 of the 27 journals have started the transition to Gold Open Access, although many editors are not aware of this shift, but they wouldn’t support it, and many are actively against it.

Exploramos aquí la conexión entre los conceptos de riesgo e igualdad en el argumento del observador imparcial. La concepción de la justicia que elegiría un observador imparcial se justifica por la pureza del procedimiento de elección. Sin embargo, si modelizamos esta decisión utilizando medidas del riesgo habituales en matemática financiera, veremos cómo el criterio de elección del observador bajo el velo de la ignorancia contiene una preferencia implícita por el grado de desigualdad resultante. Esto nos obliga a reconsiderar la pureza procedimental de la elección.

Experimental balance is usually understood as the control for the value of the conditions, other than the one under study, which are liable to affect the result of a test. We will discuss three different approaches to balance. ‘Millean balance’ requires to identify and equalize ex ante the value of these conditions in order to conduct solid causal inferences. ‘Fisherian balance’ measures ex post the influence of uncontrolled conditions through the analysis of variance. In ‘efficiency balance’ the value of the antecedent conditions is decided ex ante according to the efficiency they yield in the estimation of the treatment outcome. Against some old arguments by John Worrall, we will show that in both Fisherian and efficiency balance there are good reasons to randomize the allocation of treatments, in particular when there is no agreement among experimenters as to the antecedent conditions to be controlled for.

Este artículo estudia la justificación normativa de la adopción de los ensayos clínicos aleatorizados por parte de las autoridades sanitarias británicas como estándar metodológico en 1946. A partir de un análisis de los distintos intereses de los participantes en el proceso (pacientes, médicos, farmacéuticas y el propio Estado) argumentamos que la aleatorización se adoptó como mecanismo de asignación imparcial de tratamientos, aunque sus propiedades estadísticas no fueran bien comprendidas. Tal justificación permanece aún vigente

We defend, from a contractarian perspective, that the fair price of an insurance policy is the amount that the contracting parties agree when they are both equally uncertain about the insured event. Drawing on the approach developed by R. Sugden in _The Community of Advantage_, we answer two standard objections raised against contractarianism in the actuarial sciences: (1) people are not wise enough to assess their actuarial risks; (2) they are not rational enough to decide which insurance policy suits them better. We show under which circumstances people can make fair actuarial agreements, without presupposing any objective risk or rationality benchmarks.