Brave Sperm and Demure Eggs: Fallopian Gender Politics on YouTube

A narrative analysis of videos of human conception from medical and nonmedical sources aired in the democratic space of YouTube finds that stereotypical gender roles are consistently assigned to cellular behavior. Sperm are represented as little men and embodiments of hegemonic masculinity, with heroic sperm winning the egg prize after a competitive athletic contest fraught with peril. Eggs are represented as featureless planets floating in a murky void and are without agency or action. Almost every video is about the “journey” or “adventure” of the sperm; the egg has no adventure. These videos represent a view of a persistent gendered narrative of human fertilization that does not coalesce with emerging scientific narratives that appear to attempt to be more gender-neutral in accounts of conception. The imposition of gendered social scripts onto biology—even pop-culture biology—may work to obscure common understanding of the nature of gender and of humanity, as well as reveal vivid and enduring stereotypes

Sparse Model Identification and Learning for Ultra-high-dimensional Additive Partially Linear Models

The additive partially linear model (APLM) combines the flexibility of nonparametric regression with the parsimony of regression models, and has been widely used as a popular tool in multivariate nonparametric regression to alleviate the "curse of dimensionality". A natural question raised in practice is the choice of structure in the nonparametric part, that is, whether the continuous covariates enter into the model in linear or nonparametric form. In this paper, we present a comprehensive framework for simultaneous sparse model identification and learning for ultra-high-dimensional APLMs where both the linear and nonparametric components are possibly larger than the sample size. We propose a fast and efficient two-stage procedure. In the first stage, we decompose the nonparametric functions into a linear part and a nonlinear part. The nonlinear functions are approximated by constant spline bases, and a triple penalization procedure is proposed to select nonzero components using adaptive group LASSO. In the second stage, we refit data with selected covariates using higher order polynomial splines, and apply spline-backfitted local-linear smoothing to obtain asymptotic normality for the estimators. The procedure is shown to be consistent for model structure identification. It can identify zero, linear, and nonlinear components correctly and efficiently. Inference can be made on both linear coefficients and nonparametric functions. We conduct simulation studies to evaluate the performance of the method and apply the proposed method to a dataset on the Shoot Apical Meristem (SAM) of maize genotypes for illustration

The importance of distinct modeling strategies for gene and gene-specific treatment effects in hierarchical models for microarray data

When analyzing microarray data, hierarchical models are often used to share information across genes when estimating means and variances or identifying differential expression. Many methods utilize some form of the two-level hierarchical model structure suggested by Kendziorski et al. [Stat. Med. (2003) 22 3899-3914] in which the first level describes the distribution of latent mean expression levels among genes and among differentially expressed treatments within a gene. The second level describes the conditional distribution, given a latent mean, of repeated observations for a single gene and treatment. Many of these models, including those used in Kendziorski's et al. [Stat. Med. (2003) 22 3899-3914] EBarrays package, assume that expression level changes due to treatment effects have the same distribution as expression level changes from gene to gene. We present empirical evidence that this assumption is often inadequate and propose three-level hierarchical models as extensions to the two-level log-normal based EBarrays models to address this inadequacy. We demonstrate that use of our three-level models dramatically changes analysis results for a variety of microarray data sets and verify the validity and improved performance of our suggested method in a series of simulation studies. We also illustrate the importance of accounting for the uncertainty of gene-specific error variance estimates when using hierarchical models to identify differentially expressed genes.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS535 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

'A Slice of Life': Food Narratives and Menus from Mass-Observers in 1982 and 1945

This paper reports on an analysis of hitherto unexamined documentary data on food held within the UK Mass Observation Archive (MOA). In particular it discusses responses to the 1982 Winter Directive which asked MOA correspondents about their experiences of food and eating, and the food diaries submitted by MOA panel members in 1945. What is striking about these data is the extent to which memories of food and eating are interwoven with recollections of the lifecourse; in particular social relations, family life, and work. It seems asking people about food generates insight into aspects of everyday life. In essence, memories of food provide a crucial and potentially overlooked medium for developing an appreciation of social change. We propose the concept \'food narratives\' to capture the essence of these reflections because they reveal something more than personal stories; they are both individual and collective experiences in that personal food narratives draw upon shared cultural repertoires, generational memories, and tensions between age cohorts. Food narratives are embodied and embedded in social networks, socio-cultural contexts and socio-economic epochs. Thus the daily menus recorded in 1945 and memories scribed in 1982 do not simply communicate what people ate, liked and disliked but throw light on two contrasting moments of British history; the end of the second world war and an era of transition, reform, individualization, diversity which was taking place in the early 1980s.Mass Observation Archive; Food and Eating; Qualitative; Personal Food Narratives; Secondary Analysis; Longitudinal