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Adopting this stance is challenging because it requires the candidate or analyst to give up the idealization of psychoanalysis and often of the training analyst that can lie behind claims to exceptionalism and replace it with a realistic assessment. In this brief contribution, I revisit ideas that I have expressed over the past twenty years (e.g. Tuckett [10], [11], [12], [13], [14], [15], [16], [17], [18]; Tuckett et al. [19]) and collect them together to outline six significant and inter-related barriers currently in place which prevent psychoanalysts, on the whole, from having a productive debate with each other and also with those in other disciplines, or society more generally. As Denis puts it, "If the are not to limit themselves to indoctrinating their patients with ready-made formulas, psychoanalysts must allow themselves to be taken over by their patient's psychic functioning" ([3], 43). Denis suggests that due to their everyday clinical experience analysts find it very hard to loosen their attachment to their own model of doing psychoanalysis, in part due to what he calls the traumatic quality of their work and its emotional uncertainties, which tempts them to a fetishistic solution. [Extracted from the article]

This paper investigates the role of sentiment in the US economy from 1920 to 1934 using digitised articles from The Wall Street Journal. We derive a monthly sentiment index and use a 10‐variable vector error correction model to identify sentiment shocks that are orthogonal to fundamentals. We show the timing and strength of these shocks and their resultant effects on the economy using historical decompositions. Intermittent impacts of up to 15 per cent on industrial production, 10 per cent on the S&P 500 and bank loans, and 37 basis points for the credit risk spread suggest a large role for sentiment. [ABSTRACT FROM AUTHOR]

Whereas most commentators agree about the centrality of narratives in decision-making, the commentaries revealed little consensus about the nature of radical uncertainty. Here we consider thirteen objections to our views, including our characterization of the uncertain decision environment and associated cognitive, affective, and social processes. We conclude that under radical uncertainty, narratives rather than probabilities are the currency of thought. [ABSTRACT FROM AUTHOR]

Conviction Narrative Theory (CNT) is a theory of choice under radical uncertainty – situations where outcomes cannot be enumerated and probabilities cannot be assigned. Whereas most theories of choice assume that people rely on (potentially biased) probabilistic judgments, such theories cannot account for adaptive decision-making when probabilities cannot be assigned. CNT proposes that people use narratives – structured representations of causal, temporal, analogical, and valence relationships – rather than probabilities, as the currency of thought that unifies our sense-making and decision-making faculties. According to CNT, narratives arise from the interplay between individual cognition and the social environment, with reasoners adopting a narrative that feels "right" to explain the available data; using that narrative to imagine plausible futures; and affectively evaluating those imagined futures to make a choice. Evidence from many areas of the cognitive, behavioral, and social sciences supports this basic model, including lab experiments, interview studies, and econometric analyses. We identify 12 propositions to explain how the mental representations (narratives) interact with four inter-related processes (explanation, simulation, affective evaluation, and communication), examining the theoretical and empirical basis for each. We conclude by discussing how CNT can provide a common vocabulary for researchers studying everyday choices across areas of the decision sciences. [ABSTRACT FROM AUTHOR]

How do people form expectations about the future? We use amateur and expert investors' expectations about financial asset prices to study this question. Three experiments contrast the rational expectations assumption from neoclassical economics (investors forecast according to neoclassical financial theory) against two psychological theories of expectation formation—behaviorally informed expectations (investors understand empirical market anomalies and expect these anomalies to occur) and narrative expectations (investors use narrative thinking to predict future prices). Whereas neoclassical financial theory maintains that past public information cannot be used to predict future prices, participants used company performance information revealed before a base price quotation to project future price trends after that quotation (Experiment 1), contradicting rational expectations. Importantly, these projections were stronger when information concerned predictions about a company's future performance rather than actual data about its past performance, suggesting that people not only rely on financially irrelevant (but narratively relevant) information for making predictions but erroneously impose temporal order on that information. These biased predictions had downstream consequences for asset allocation choices (Experiment 2), and these choices were driven in part by affective reactions to the company performance news (Experiment 3). There were some mild effects of expertise, but overall the effects of narrative appear to be consistent across all levels of expertise studied, including professional financial analysts. We conclude by discussing the prospects for a narrative theory of choice that provide new microfoundational insights about economic behavior. [ABSTRACT FROM AUTHOR]

The growing ecosystem of peer-to-peer enterprise – the Sharing Economy (SE) – has brought with it a substantial change in how we access and provide goods and services. Within the SE, individuals make decisions based mainly on user-generated trust and reputation information (TRI). Recent research indicates that the use of such information tends to produce a positivity bias in the perceived trustworthiness of fellow users. Across two experimental studies performed on an artificial SE accommodation platform, we test whether users' judgments can be accurate when presented with diagnostic information relating to the quality of the profiles they see or if these overly positive perceptions persist. In study 1, we find that users are quite accurate overall (70%) at determining the quality of a profile, both when presented with full profiles or with profiles where they selected three TRI elements they considered useful for their decision-making. However, users tended to exhibit an "upward quality bias" when making errors. In study 2, we leveraged patterns of frequently vs. infrequently selected TRI elements to understand whether users have insights into which are more diagnostic and find that presenting frequently selected TRI elements improved users' accuracy. Overall, our studies demonstrate that – positivity bias notwithstanding – users can be remarkably accurate in their online SE judgments. [ABSTRACT FROM AUTHOR]

Substantial differences in productivity, accompanied by growing social and political discontent, have widened across UK regions in the last 40 years, creating a dysfunctional spatial equilibrium; a coordination failure that has so far proved resistant to change. In this paper, we link such persistent regional disequilibria with current socio-psychological theories about the role of narrative in decision-making under radical uncertainty to explore how and why ideas held collectively within a social network can become the coordinating device for a range of decisions within networked communities that have extra-market effects (externalities), analogous to the role that prices play within markets. Drawing on findings from a pilot interview study in two UK regions, we show the potential for local leadership to use well-constructed narratives to coordinate fragmented agents to cooperate on a common purpose and more generally propose a framework to understand how low-income equilibria become stable but might be re-set. In this way we bring new insights into the need for an expanded economic theory of knowledge applicable to expectation and preference formation in conditions of radical uncertainty. [ABSTRACT FROM AUTHOR]

We study the psychology at the intersection of two social trends. First, as markets become increasingly specialized, consumers must increasingly defer to outside experts to decide among complex products. Second, people divide themselves increasingly into moral tribes, defining themselves in terms of shared values with their group and often seeing these values as being objectively right or wrong. We tested how and why these tribalistic tendencies affect consumers' willingness to defer to experts. We find that consumers are indeed tribalistic in which experts they find convincing, preferring products advocated by experts who share their moral values (Study 1), with this effect generalizing across product categories (books and electronics) and measures (purchase intentions, information‐seeking, willingness‐to‐pay, product attitudes, and consequential choices). We also establish the mechanisms underlying these effects: because many consumers believe moral matters to be objective facts, experts who disagree with those values are seen as less competent and therefore less believable (Studies 2 and 3), with this effect strongest among consumers who are high in their belief in objective moral truth (Study 4). Overall, these studies seek not only to establish dynamics of tribalistic deference to experts but also to identify which consumers are more or less likely to fall prey to these tribalistic tendencies. [ABSTRACT FROM AUTHOR]

Psychoanalytic training has been an object of controversy for many years. Arguments have been intense about the details, sometimes called "requirements", and particularly over whether or not training institutes should have routine external validation. We describe these arguments and present preliminary conclusions about the core challenges psychoanalytic trainings face using a unique set of detailed observations collected during structured "conversations" inside nine European institutes. We conclude that whether a psychoanalytic training is "working" is not a matter of compliance with requirements. Rather, it is an issue of how candidates, training analysts, supervisors and committee members, confront within and between each other the consequences of the unconscious dynamics that psychoanalytic training must inevitably create. Institutional psychoanalytic capacity is to take itself as the object. Consequentially, we propose that training committees that seek to claim that their psychoanalytic training is genuinely and safely producing psychoanalysts would be ones that institute routine procedures to show to themselves, transparently, how they attend to the dynamics just mentioned and how they take a neutral inquisitive stance towards them. Fear of oversight, we suggest, is a symptom of deeper anxieties. They can be faced by creating an appropriate setting. Properly conducted visits from outsiders are welcomed. [ABSTRACT FROM AUTHOR]

This contribution is a personal reflection on the papers presented at the New York and London anniversary conferences, in which the author takes stock to consider what they might tell us about where the discipline is now, where it has come from and where it might go. Taking the clinical contributions as evidence of the way many leading analysts in the field now proceed, it is suggested that there is an increasing and more and more subtle use of the analyst's behaviour, thoughts, fantasies, feelings and experiences, inside and outside the session, as core sources for constructing the patient's unconscious. Placing this observation in the context of issues of evidence raised in the 50th and 75th anniversary volumes, the author argues that a possible future agenda for the field may be to think more plainly about the basis of an analyst's knowledge claims, whether made implicitly or explicitly to patients in sessions. The author wonders if more disciplined understanding of transference consistent with neuroscientific findings of the last few years may be one factor that could prove useful. [ABSTRACT FROM AUTHOR]

This contribution to honour the Journal's centenary elaborates the classical view that what is primarily at stake in a psychoanalysis are ideas patients and analysts have that are prevented from becoming conscious. It is argued, drawing on a "bare bones" or parsimonious model of psychoanalytic treatment, that the ideas concerned are mainly the worrying unconscious beliefs patients have about their experience with their analysts. These are ideas saturated with feeling and derived from the internal templates that patients use to respond to current experience, based on ways they have registered experience from the beginning of their lives. Because such ideas are unconscious, they cannot be taken as hypotheses until revised. Rather, they are assumed to be facts, knowledge of which, because they generate feelings like anxiety, guilt or shame, is to be avoided and hidden. After introducing the model and discussing two short vignettes from psychoanalytic treatment, the author elaborates the view that recognising which ideas are being prevented from becoming conscious in sessions is the kernel of psychoanalytic therapy. [ABSTRACT FROM AUTHOR]

What psychoanalysts consider psychoanalytic interpretation, in what setting it emerges and specifically why, when and how transference should be interpreted, have become increasingly unclear and controversial. In this paper I set out, elaborate, illustrate and argue the value for post-session reflection, certainly within the object relations traditions, of adopting a parsimonious model of practice. The model rests on the foundations of a specific understanding of free association, evenly suspended attention, resistance and transference and separating two epistemologically distinct intentions in transference interpretation. One, transference construction, aims to make a patient aware of the unconscious ways a patient is behaving in sessions (and then outside them) and how and why that is happening. A second, transference designation, focuses on the more limited aim of making patients aware of how they unconsciously experience the psychoanalyst at specific moments of resistance in sessions. Both types of interpretation may help but, I argue, it is the latter that must form the bedrock for fundamental change. [ABSTRACT FROM AUTHOR]

The Sharing Economy (SE) is a growing ecosystem focusing on peer-to-peer enterprise. In the SE the information available to assist individuals (users) in making decisions focuses predominantly on community-generated trust and reputation information. However, how such information impacts user judgement is still being understood. To explore such effects, we constructed an artificial SE accommodation platform where we varied the elements related to hosts’ digital identity, measuring users’ perceptions and decisions to interact. Across three studies, we find that trust and reputation information increases not only the users’ perceived trustworthiness, credibility, and sociability of hosts, but also the propensity to rent a private room in their home. This effect is seen when providing users both with complete profiles and profiles with partial user-selected information. Closer investigations reveal that three elements relating to the host’s digital identity are sufficient to produce such positive perceptions and increased rental decisions, regardless of which three elements are presented. Our findings have relevant implications for human judgment and privacy in the SE, and question its current culture of ever increasing information-sharing. [ABSTRACT FROM AUTHOR]

We propose conviction narrative theory (CNT) to broaden decision-making theory in order to better understand and analyse how subjectively means–end rational actors cope in contexts in which the traditional assumptions in decision-making models fail to hold. Conviction narratives enable actors to draw on their beliefs, causal models, and rules of thumb to identify opportunities worth acting on, to simulate the future outcome of their actions, and to feel sufficiently convinced to act. The framework focuses on how narrative and emotion combine to allow actors to deliberate and to select actions that they think will produce the outcomes they desire. It specifies connections between particular emotions and deliberative thought, hypothesising that approach and avoidance emotions evoked during narrative simulation play a crucial role. Two mental states, Divided and Integrated, in which narratives can be formed or updated, are introduced and used to explain some familiar problems that traditional models cannot. [ABSTRACT FROM AUTHOR]

The financial crisis of 2008 was unforeseen partly because the academic theories that underpin policy making do not sufficiently account for uncertainty and complexity or learned and evolved human capabilities for managing them. Mainstream theories of decision making tend to be strongly normative and based on wishfully unrealistic “idealized” modeling. In order to develop theories of actual decision making under uncertainty, we need new methodologies that account for how human (sentient) actors often manage uncertain situations “well enough.” Some possibly helpful methodologies, drawing on digital science, focus on the role of emotions in determining people's choices; others examine how people construct narratives that enable them to act; still others combine qualitative with quantitative data. [ABSTRACT FROM PUBLISHER]

Financial assets are abstract entities. Their value depends on beliefs which are inherently social and, we argue, emotional. Recent events have revealed profound uncertainty at the heart of financial markets, the manifest existence of emotion and theway confidence is crucial to orderly market functioning. Using findings from two interview studies, supported by ethnographic observation, we elaborate on the irreducible cognitive and emotional conflicts which face actors engaged in financial markets and threaten their daily operations. We introduce the term conviction narrative to analyse howthey manage these conflicts on a day-to-day basis, and with what collective consequences. Our thesis is that expertise and conviction in financial markets have constantly to be created and renewed through a combination of psychological and social action with the implication at the macro level that while financial markets can be orderly they are so in an intrinsically fragile way. [ABSTRACT FROM AUTHOR]

The article presents an obituary for Betty Joseph, an acclaimed teacher and supervisor.

Noise in quantum computing is countered with quantum error correction. Achieving optimal performance will require tailoring codes and decoding algorithms to account for features of realistic noise, such as the common situation where the noise is biased towards dephasing. Here we introduce an efficient high-threshold decoder for a noise-tailored surface code based on minimum-weight perfect matching. The decoder exploits the symmetries of its syndrome under the action of biased noise and generalizes to the fault-tolerant regime where measurements are unreliable. Using this decoder, we obtain fault-tolerant thresholds in excess of 6% for a phenomenological noise model in the limit where dephasing dominates. These gains persist even for modest noise biases: we find a threshold of ~5% in an experimentally relevant regime where dephasing errors occur at a rate 100 times greater than bit-flip errors. [ABSTRACT FROM AUTHOR]

We show that a simple modification of the surface code can exhibit an enormous gain in the error correction threshold for a noise model in which Pauli Z errors occur more frequently than X or Y errors. Such biased noise, where dephasing dominates, is ubiquitous in many quantum architectures. In the limit of pure dephasing noise we find a threshold of 43.7(1)% using a tensor network decoder proposed by Bravyi, Suchara, and Vargo. The threshold remains surprisingly large in the regime of realistic noise bias ratios, for example 28.2(2)% at a bias of 10. The performance is, in fact, at or near the hashing bound for all values of the bias. The modified surface code still uses only weight-4 stabilizers on a square lattice, but merely requires measuring products of Y instead of Z around the faces, as this doubles the number of useful syndrome bits associated with the dominant Z errors. Our results demonstrate that large efficiency gains can be found by appropriately tailoring codes and decoders to realistic noise models, even under the locality constraints of topological codes. [ABSTRACT FROM AUTHOR]