On shifting ground: First-time parents’ ideal world of paid work and family time

We examined first-time fathers’ and mothers’ perspectives about their ideal world of support in the context of dominant social ideology, ethno-cultural ideals, and the pragmatics of their everyday family, workplace, and socioeconomic circumstances during their first 18 months as parents. Twelve Canadian-born and six Chinese immigrant couples participated in individual in-depth interviews. We conducted a three-part analysis: fathers’ perspectives, mothers’ perspectives, and couples’ perspectives. Fathers focused on fulfilling dual fathering ideals of ‘time with family’ and ‘providing for family’; mothers emphasized fulfilling a mothering ideal of ‘caring for children'. Examining couples’ perspectives revealed a more nuanced understanding of their shared focus on ‘caring for family'. Parents in this study found the current social ideal of the ‘new’ father, who is both financial provider and nurturing co-parent, appealing, yet difficult to achieve. Couples wanted informal (i.e. family and social network) support, along with formal (i.e. workplace and childcare) support to enable them to provide family care and financial stability for their family. Findings contribute to understanding family and paid work experiences and decision-making among couples as new parents. We offer insights into the complexity of intersections among social ideals, personal expectations, family care, and paid work for fathers and mothers.     

Keep the hope alive: young Indonesian musicians’ views of the future

Using ethnographic and interview data, this article explores hopes for the future of young Indonesian musicians. The young people are seen to consider their future trajectories in multiple, hierarchical music fields. The article also takes into account the ontological insecurity of jobs as a professional musician, arguing that there is continuous reproduction of a doxa, namely ‘survival of the fittest’ in Indonesia. Yet despite abundant risks to livelihoods, young Indonesian musicians expressed optimistic views about the future. The analysis of data below bridges the gap between the traditionally separate youth studies fields of youth transitions and youth cultures. Our interpretation critically contextualises the dialogue between these two fields based on the experiences of young Indonesian musicians as a part of the Global South.     

How Visual is Visual Prediction?

Infants are readily able to use their recent experience to shape their future behavior. Recent work has confirmed that infants generate neural predictions based on their recent experience (Emberson, Richards, & Aslin, 2015) and that neural predictions trigger visual system activity similar to that elicited by visual stimulation. This study uses behavioral methods to ask, how visual is visual prediction? In Experiment 1, we confirmed that when additional trials provide additional visual experience with the experimental shape, infants exhibit a robust novelty preference. In Experiment 2, we removed the visual stimulus from some trials and presented the predictive auditory cue alone, allowing the effects of neural prediction to be assessed. We found no evidence of looking preferences at test, suggesting that visual prediction does not contribute to the computation of visual familiarity. In Experiment 3, we provided infants with a degraded visual stimulus to test whether visual prediction could bias visual perception under ambiguous conditions. Again, we found no evidence of looking preferences at test, suggesting that visual prediction is not biasing perception of an uncertain stimulus. Overall, our results suggest that visual prediction is not visual, in the strictest sense, despite the presence of visual system activation.     

A Mixed-Methods Inquiry Into Trans* Environmental Microaggressions on College Campuses: Experiences and Outcomes

ABSTRACT

The experiences, including with environmental microaggressions, and well-being of trans* collegians remain an under-researched topic. In this mixed-methods study of a survey sample of 152 trans* collegians, multivariable regression findings suggest that the frequency of experiencing select trans* environmental microaggressions (e.g., not having access to comfortable bathrooms as a trans* person) are associated with increased risk for poorer academic outcomes (e.g., developmental challenges) but are not associated with mental health outcomes. Furthermore, interviews with 18 trans* collegians suggest that students face several systemic microaggressions, including difficulties advancing trans* inclusion. Various reactions, including paths of resistance, were identified. Implications are discussed.     

Differences in Experiences of Discrimination in Accessing Social Services Among Transgender/Gender Nonconforming Individuals by (Dis)Ability

Transgender and gender nonconforming (GNC) individuals frequently experience discrimination and potentially a lack of respect from service providers, suggesting they have decreased access to professionals with cultural competency. Similarly, people with disabilities experience higher levels of discrimination in social services than their nondisabled counterparts. From an intersectional perspective, this study examines rates of discrimination in accessing social services faced by transgender and GNC people, comparing across ability. Data indicate that although transgender and GNC individuals of all abilities experience gender-based discrimination when accessing social services, those with disabilities experience higher levels of antitransgender discrimination in mental health centers, rape crisis centers, and domestic violence shelters.     

The expected and unexpected media effects on youth’s (mis)perceptions of peer norms: Chinese college students’ overestimation of peer smoking prevalence

Youth’s perceptions of peer norms have profound effects on their attitudes and behaviors. Unfortunately, their perceptions of peers tend to be biased. To investigate the role of media in the formation of misperceived peer norms, the current study tested and compared two media-effect mechanisms: the direct exemplar mechanism and the indirect influence of presumed influence (IPI) mechanism. The two mechanisms were tested in a sample (n = 1746) that is representative of college students in one large university in China, based on which the actual and perceived campus smoking rates were examined. The individual-level perceived peer smoking prevalence was then analyzed in comparison with the campus-level actual smoking prevalence. The results revealed serious overestimations of peer smoking prevalence. As predicted, pro-smoking media content significantly heightened smoking prevalence estimates through both exemplar and IPI mechanisms. In contrast, anti-smoking messages did not elicit any intended effect through the IPI mechanism, but showed a boomerang effect through the exemplar mechanism. These findings suggest that both pro- and anti-smoking media content may be responsible for inflated perceptions of peer smoking among youth.     

Comparison of dichotomized and distributional approaches in rare event clinical trial design: a fixed Bayesian design

This research was motivated by our goal to design an efficient clinical trial to compare two doses of docosahexaenoic acid supplementation for reducing the rate of earliest preterm births (ePTB) and/or preterm births (PTB). Dichotomizing continuous gestational age (GA) data using a classic binomial distribution will result in a loss of information and reduced power. A distributional approach is an improved strategy to retain statistical power from the continuous distribution. However, appropriate distributions that fit the data properly, particularly in the tails, must be chosen, especially when the data are skewed. A recent study proposed a skew-normal method. We propose a three-component normal mixture model and introduce separate treatment effects at different components of GA. We evaluate operating characteristics of mixture model, beta-binomial model, and skew-normal model through simulation. We also apply these three methods to data from two completed clinical trials from the USA and Australia. Finite mixture models are shown to have favorable properties in PTB analysis but minimal benefit for ePTB analysis. Normal models on log-transformed data have the largest bias. Therefore we recommend finite mixture model for PTB study. Either finite mixture model or beta-binomial model is acceptable for ePTB study.     

Functional analysis of high-content high-throughput imaging data

High-content automated imaging platforms allow the multiplexing of several targets simultaneously to generate multi-parametric single-cell data sets over extended periods of time. Typically, standard simple measures such as mean value of all cells at every time point are calculated to summarize the temporal process, resulting in loss of time dynamics of the single cells. Multiple experiments are performed but observation time points are not necessarily identical, leading to difficulties when integrating summary measures from different experiments. We used functional data analysis to analyze continuous curve data, where the temporal process of a response variable for each single cell can be described using a smooth curve. This allows analyses to be performed on continuous functions, rather than on original discrete data points. Functional regression models were applied to determine common temporal characteristics of a set of single cell curves and random effects were employed in the models to explain variation between experiments. The aim of the multiplexing approach is to simultaneously analyze the effect of a large number of compounds in comparison to control to discriminate between their mode of action. Functional principal component analysis based on T-statistic curves for pairwise comparison to control was used to study time-dependent compound effects.     

FDR control of detected regions by multiscale matched filtering

Feature extraction from observed noisy samples is a common important problem in statistics and engineering. This paper presents a novel general statistical approach to the region detection problem in long data sequences. The proposed technique is a multiscale kernel regression in conjunction with statistical multiple testing for region detection while controlling the false discovery rate (FDR) and maximizing the signal-to-noise ratio via matched filtering. This is achieved by considering a one-dimensional region detection problem as its equivalent zero-dimensional peak detection problem. The detection method does not require a priori knowledge of the shape of the nonzero regions. However, if the shape of the nonzero regions is known a priori, e.g., rectangular pulse, the signal regions can also be reconstructed from the detected peaks, seen as their topological point representatives. Simulations show that the method can effectively perform signal detection and reconstruction in the simulated data under high noise conditions, while controlling the FDR of detected regions and their reconstructed length.     

Estimating function method for product autoregressive models

The first-order product autoregressive (PAR(1)) model introduced by McKenzie in 1982 McKenzie, E. D. (1982). Product autoregression: A time series characterization of the gamma distribution. Journal of Applied Probability 19:463–468. [Google Scholar] did not attract the attention of practitioners due to the unavailability of a proper estimation method. This article proposes an estimating function (EF) method to fill the gap. In particular, we suggest an optimal combination of linear and quadratic EFs to overcome the problem of parameter identification. The procedure is applied to Weibull and Gamma PAR(1) models. Simulation and data analysis show that the proposed method performs better than the existing methods.