He Said, She Said: Gender Differences in the Disclosure of Positive and Negative Information

Research on gender differences in (self-)disclosure has produced mixed results, and, where differences have emerged, they may be an artifact of the measures employed. The present paper explores whether gender – defined as self-identified membership in one’s sociocultural group – can indeed account for differences in the desire and propensity to divulge information to others. We additionally identify a possible moderator for such differences. In three studies employing two distinct research approaches – a free recall task for the extreme desire to disclose (Study 1, N = 195) and scaled responses to scenarios that manipulate valence experimentally in an exploratory study (Study 2, N = 547) and a preregistered replication (Study 3, N = 405) – we provide evidence of a robust interaction between gender and information valence. Male participants appear similar to female participants in their desire and likelihood to disclose positive information but are less likely than women to want to share negative information with others, and less likely to ultimately act on that desire. Men are reportedly more motivated than women to disclose as a means of self-enhancement, and self-reports reveal that women perceive their sharing behavior to be relatively normative, while men believe themselves to be more withholding than what is optimal. Information disclosure is increasingly pervasive and permanent in the digital age, and is accompanied by an array of social and psychological consequences. Given their disparate disclosing behaviors, men and women may thus be differentially advantaged by, or susceptible to, the positive and negative consequences of information sharing

Surface gravity wave-induced drift of floating objects in the diffraction regime

Floating objects will drift due to the action of surface gravity waves. This drift will depart from that of a perfect Lagrangian tracer due to both viscous effects (non-potential flow) and wave–body interaction (potential flow). We examine the drift of freely floating objects in regular (non-breaking) deep-water wave fields for object sizes that are large enough to cause significant diffraction. Systematic numerical simulations are performed using a hybrid numerical solver, qaleFOAM, which deals with both viscosity and wave–body interaction. For very small objects, the model predicts a wave-induced drift equal to the Stokes drift. For larger objects, the drift is generally greater and increases with object size (we examine object sizes up to 10% of the wavelength). The effects of different shapes, sizes and submergence depths and steepnesses are examined. Furthermore, we derive a ‘diffraction-modified Stokes drift’ akin to Stokes (Trans. Camb. Phil. Soc., vol. 8, 1847, pp. 411–455), but based on the combination of incident, diffracted and radiated wave fields, which are based on potential-flow theory and obtained using the boundary element method. This diffraction-modified Stokes drift explains both qualitatively and quantitatively the increase in drift. Generally, round objects do not diffract the wave field significantly and do not experience a significant drift enhancement as a result. For box-shape objects, drift enhancement is greater for larger objects with greater submergence depths (we report an increase of 92% for simulations without viscosity and 113% with viscosity for a round-cornered box whose size is 10% of the wavelength). We identify the specific standing wave pattern that arises near the object because of diffraction as the main cause of the enhanced drift. Viscosity plays a small positive role in the enhanced drift behaviour of large objects, increasing the drift further by approximately 20%

Reallocation with priorities

We consider a reallocation problem with priorities where each agent is initially endowed with a house and is willing to exchange it but each house has a priority ordering over the agents of the market. In this setting, it is well known that there is no individually rational and stable mechanism. As a result, the literature has introduced a modified stability notion called μ0-stability. In contrast to college admission problems, in which prioritie s are present but there is no initial endowment, we show that the ownership-adjusted Deferred Acceptance mechanism identified in the literature is not the only individually rational, strategy-proof and μ0-stable mechanism. By introducing a new axiom called the independence of irrelevant agents and using the standard axiom of unanimity, we show that the ownership-adjusted Deferred Acceptance mechanism is the unique mechanism that is individually rational, strategy-proof, μ0-stable, unanimous and independent of irrelevant agents

Intimate partner violence and children's health outcomes

A growing body of literature has established that childhood health is a crucial determinant of human capital formation. Shocks experienced in utero and during early life may have far-reaching consequences that extend well into adulthood. Nevertheless, there is relatively little evidence regarding the effects of parental behaviour on child health. This paper contributes to the literature by examining the impact of intimate partner violence (IPV) on the child's health production function. Using data from the UK's Millennium Cohort Study and leveraging information on both child health and IPV, our analysis reveals that exposure to IPV is negatively associated to child's health. Children witnessing IPV in their household see their probability of being in excellent health reduced by 7 percentage points. Our results also suggest that children exposed to IPV are subject to increased morbidity, manifested in elevated risks of hearing and respiratory problems, as well as long-term health conditions and are less likely to get fully immunised

Three Approaches for Winning the Platform Competition

The notion of platforms isn't novel, yet digital platforms have become the dominant business models across various industries. Today, many of the world's most valuable companies are platform-based, deriving their success from disrupting conventional businesses and innovating new products and services in emerging areas. Digital platforms are not exclusive to tech giants or digital startups. Companies in established sectors, such as banking, automotive, pharmaceuticals, airlines, and retail, are increasingly leveraging digital platforms to transform their operations and industries, with many already delivering remarkable results. Digital platforms are fundamentally reshaping strategy and competition. Unlike traditional manufacturing or product-centric organizations, the unique attributes of platforms, like network effects and winner-takes-all market dynamics, create a fiercely competitive environment, making it particularly challenging when competing against platform leaders with formidable capabilities and resources and dominant market positions. This study delves into critical questions: What are the main strategies used by platforms to gain market dominance? How do emerging platforms challenge and overtake established ones? Under what conditions are these strategies successful? Addressing these questions is essential for business leaders, entrepreneurs, and policymakers, and they constitute the central focus of this research

Assessment of perinatal anxiety: diagnostic accuracy of five measures

Background Anxiety in pregnancy and after giving birth (the perinatal period) is highly prevalent but under-recognised. Robust methods of assessing perinatal anxiety are essential for services to identify and treat women appropriately. Aims To determine which assessment measures are most psychometrically robust and effective at identifying women with perinatal anxiety (primary objective) and depression (secondary objective). Method We conducted a prospective longitudinal cohort study of 2243 women who completed five measures of anxiety and depression (Generalized Anxiety Disorder scale (GAD) two- and seven-item versions; Whooley questions; Clinical Outcomes in Routine Evaluation (CORE-10); and Stirling Antenatal Anxiety Scale (SAAS)) during pregnancy (15 weeks, 22 weeks and 31 weeks) and after birth (6 weeks). To assess diagnostic accuracy a sample of 403 participants completed modules of the Mini-International Neuropsychiatric Interview (MINI). Results The best diagnostic accuracy for anxiety was shown by the CORE-10 and SAAS. The best diagnostic accuracy for depression was shown by the CORE-10, SAAS and Whooley questions, although the SAAS had lower specificity. The same cut-off scores for each measure were optimal for identifying anxiety or depression (SAAS ≥9; CORE-10 ≥9; Whooley ≥1). All measures were psychometrically robust, with good internal consistency, convergent validity and unidimensional factor structure. Conclusions This study identified robust and effective methods of assessing perinatal anxiety and depression. We recommend using the CORE-10 or SAAS to assess perinatal anxiety and the CORE-10 or Whooley questions to assess depression. The GAD-2 and GAD-7 did not perform as well as other measures and optimal cut-offs were lower than currently recommended

Public inquiries into conflict and security: Scandals, archives, and the politics of epistemology

Public inquiries into matters of conflict and security are vitally important yet undertheorised. This article explores the potential of inquiries for the democratic scrutiny of foreign policy, military doctrine, and grand strategy. In recent decades, there have been numerous inquiries into contentious foreign and security policy incidents in Britain, a trend reflected elsewhere in global politics. Inquiries can unveil facts, identify lessons, and rebuild trust. But critics claim that inquiries overlook systemic flaws. Our analysis transcends the usual arguments for or against public inquiries by explaining how inquiries produce knowledge and how this could be improved. We argue that inquiries necessarily involve the following three distinct processes: scandalisation, archivisation, and epistemology. We suggest how future inquiries could overcome extant limitations through a broader scope, diversification of evidence, and methodological pluralism. Such inquiries can play an improved role in promoting reflection and dialogue about a just international order and Britain’s role within it

Detecting Respiratory Viruses Using a Portable NIR Spectrometer—A Preliminary Exploration with a Data Driven Approach

Respiratory viruses’ detection is vitally important in coping with pandemics such as COVID-19. Conventional methods typically require laboratory-based, high-cost equipment. An emerging alternative method is Near-Infrared (NIR) spectroscopy, especially a portable one of the type that has the benefits of low cost, portability, rapidity, ease of use, and mass deployability in both clinical and field settings. One obstacle to its effective application lies in its common limitations, which include relatively low specificity and general quality. Characteristically, the spectra curves show an interweaving feature for the virus-present and virus-absent samples. This then provokes the idea of using machine learning methods to overcome the difficulty. While a subsequent obstacle coincides with the fact that a direct deployment of the machine learning approaches leads to inadequate accuracy of the modelling results. This paper presents a data-driven study on the detection of two common respiratory viruses, the respiratory syncytial virus (RSV) and the Sendai virus (SEV), using a portable NIR spectrometer supported by a machine learning solution enhanced by an algorithm of variable selection via the Variable Importance in Projection (VIP) scores and its Quantile value, along with variable truncation processing, to overcome the obstacles to a certain extent. We conducted extensive experiments with the aid of the specifically developed algorithm of variable selection, using a total of four datasets, achieving classification accuracy of: (1) 0.88, 0.94, and 0.93 for RSV, SEV, and RSV + SEV, respectively, averaged over multiple runs, for the neural network modelling of taking in turn 3 sessions of data for training and the remaining one session of an ‘unknown’ dataset for testing. (2) the average accuracy of 0.94 (RSV), 0.97 (SEV), and 0.97 (RSV + SEV) for model validation and 0.90 (RSV), 0.93 (SEV), and 0.91 (RSV + SEV) for model testing, using two of the datasets for model training, one for model validation and the other for model testing. These results demonstrate the feasibility of using portable NIR spectroscopy coupled with machine learning to detect respiratory viruses with good accuracy, and the approach could be a viable solution for population screening

Trading HIV for Sheep: Risky sexual behaviour and the response of female sex workers to Tabaski in Senegal

We use a cohort of female sex workers in Senegal to show how large anticipated economic shocks lead to increased risky sexual behaviour. Exploiting the exogenous timing of interviews, we study the effect of Tabaski, the most important Islamic festival celebrated in Senegal, in which most households purchase an animal for sacrifice. Condom use, measured robustly via the list experiment, falls by between 27.3pp (65.5%) and 43.1pp (22.7%) in the 9 days before Tabaski, or a maximum of 49.5pp (76%) in the week block preceding Tabaski. The evidence suggests the economic pressures from Tabaski are key to driving the behaviour change observed in the context that condomless sex commands a price premium. Those most exposed to the economic pressure from Tabaski were unlikely to be using condoms at all in the week before the festival. Our findings show that Tabaski leads to increased risky behaviours for female sex workers, a key population at high risk of HIV infection, for at least one week every year and has implications for FSWs in all countries celebrating Tabaski or similar festivals. Because of the scale, frequency, and size of the behavioural response to shocks of this type, policy should be carefully designed to protect vulnerable women against anticipated shocks

Off-design performance assessment of an axial turbine for a 100 MWe concentrated solar power plant operating with CO2 mixtures

This paper presents an investigation of the aerodynamic performance of a 130 MW axial turbine operating with a CO2/SO2 mixture using a mean-line off-design performance model; where the validity of this model has been confirmed through verification against results from the literature and computational fluid dynamic (CFD) simulations. This analysis also includes assessing the impact of varying the number of stages on the part-load operation. Additionally, the application of similitude theory to non-dimensionalise performance characteristics is validated by assessing the performance of the same turbine with different working fluids, mixture compositions, and rotational speeds. The mean-line performance model applied throughout this study is based on the Aungier loss model, whilst a multi-stage, Reynolds averaged CFD model is employed to assess the 3D flow behaviour using the turbulence model. Significant deviations in total-to-total efficiency were observed between the mean-line and CFD results during part-load operation, especially at lower mass flow rates. These deviations can reach up to 18% when the blade Mach number exceeds the design point by 12%. This is attributed to flow separation, which is evident from the CFD simulations, and the mean-line loss model fails to predict. From a purely aerodynamic standpoint, the turbine can operate at part-load conditions up to 88.5% of the design flow coefficient based on the CFD results and achieve an efficiency of 80.2%. It was also found that increasing the number of stages from 4 to 14 can improve the off-design total-to-total efficiency by approximately 7.7% at 93% of the design flow coefficient. This demonstrates that increasing the number of stages enhances turbine performance at both design and part-load operations. Finally, the similitude scaling laws formulated using real-gas equation of state were found to remain valid for all the mixtures, molar compositions, and operating conditions considered