Work-Family Conflict and Gender Equality: Theory Development, Responses of Policy Regimes, and Immigrants' Experiences

Indiana University-Purdue University Indianapolis (IUPUI)Working parents across countries perceive increased work-family conflict. Workfamily conflict not only has detrimental effect on the well-being of individuals, families, and organizations, but also contributes to gender inequality and care crisis in society. This dissertation consists of three studies that examine work-family conflict in terms of theory, policy, and understudied populations. The first study examined theories of workfamily conflict through critical realism and gender lenses. Based on an in-depth critique of current theoretical and empirical evidence, an integrated-theoretical framework informed by role theory, gendered organization theory, and the ecology of the gendered life course approach was developed. The second study comparatively ranked OECD countries’ statutory policies of parental leave, early childhood education and care, and flexible work arrangements, in terms of their levels of supportiveness and gender equality based on the Supportiveness Index and Gender Equality Index. Among 33 countries, Sweden ranks 1st based on both indices, while the United States ranks 30th for Supportiveness and 29th for Gender Equality. Mexico, Switzerland, and Turkey rank last for both indices. A new typology of four policy regimes was further constructed based on a care-employment analytic framework using secondary qualitative and quantitative data. This new set of regime types represents countries’ varied abilities to help parents reconcile work and family demands, while promoting gender equality. The third study is a systematic review of immigrants’ experiences of work-family conflict in the U.S. Four categories of factors associated with immigrants’ work-family conflict were identified: 1) work-domain factors, 2) family-domain factors, 3) health outcomes, and 4) immigration, acculturation, and gender roles. Job demands are positively associated with work-family conflict, while having job control and job support are negatively associated with work-family conflict. More domestic work demands and economic responsibilities in the family domain have contributed to work-family conflict, whereas having domestic support for childcare and housework has mitigated it. Workfamily conflict has contributed to deteriorating physical and mental health outcomes among immigrants. Finally, this study revealed that immigration per se has uniquely shaped immigrants’ work-family interactions. Social work implications of the three studies were discussed to better address work-family conflict and related gender inequality.2020-08-2

Reduction from Complementary-Label Learning to Probability Estimates

Complementary-Label Learning (CLL) is a weakly-supervised learning problem that aims to learn a multi-class classifier from only complementary labels, which indicate a class to which an instance does not belong. Existing approaches mainly adopt the paradigm of reduction to ordinary classification, which applies specific transformations and surrogate losses to connect CLL back to ordinary classification. Those approaches, however, face several limitations, such as the tendency to overfit or be hooked on deep models. In this paper, we sidestep those limitations with a novel perspective--reduction to probability estimates of complementary classes. We prove that accurate probability estimates of complementary labels lead to good classifiers through a simple decoding step. The proof establishes a reduction framework from CLL to probability estimates. The framework offers explanations of several key CLL approaches as its special cases and allows us to design an improved algorithm that is more robust in noisy environments. The framework also suggests a validation procedure based on the quality of probability estimates, leading to an alternative way to validate models with only complementary labels. The flexible framework opens a wide range of unexplored opportunities in using deep and non-deep models for probability estimates to solve the CLL problem. Empirical experiments further verified the framework's efficacy and robustness in various settings

Achieving Maximum Distance Separable Private Information Retrieval Capacity With Linear Codes

We propose three private information retrieval (PIR) protocols for distributed storage systems (DSSs) where data is stored using an arbitrary linear code. The first two protocols, named Protocol 1 and Protocol 2, achieve privacy for the scenario with noncolluding nodes. Protocol 1 requires a file size that is exponential in the number of files in the system, while Protocol 2 requires a file size that is independent of the number of files and is hence simpler. We prove that, for certain linear codes, Protocol 1 achieves the maximum distance separable (MDS) PIR capacity, i.e., the maximum PIR rate (the ratio of the amount of retrieved stored data per unit of downloaded data) for a DSS that uses an MDS code to store any given (finite and infinite) number of files, and Protocol 2 achieves the asymptotic MDS-PIR capacity (with infinitely large number of files in the DSS). In particular, we provide a necessary and a sufficient condition for a code to achieve the MDS-PIR capacity with Protocols 1 and 2 and prove that cyclic codes, Reed-Muller (RM) codes, and a class of distance-optimal local reconstruction codes achieve both the finite MDS-PIR capacity (i.e., with any given number of files) and the asymptotic MDS-PIR capacity with Protocols 1 and 2, respectively. Furthermore, we present a third protocol, Protocol 3, for the scenario with multiple colluding nodes, which can be seen as an improvement of a protocol recently introduced by Freij-Hollanti et al.. Similar to the noncolluding case, we provide a necessary and a sufficient condition to achieve the maximum possible PIR rate of Protocol 3. Moreover, we provide a particular class of codes that is suitable for this protocol and show that RM codes achieve the maximum possible PIR rate for the protocol. For all three protocols, we present an algorithm to optimize their PIR rates.Comment: This work is the extension of the work done in arXiv:1612.07084v2. The current version introduces further refinement to the manuscript. Current version will appear in the IEEE Transactions on Information Theor

An MDS-PIR Capacity-Achieving Protocol for Distributed Storage Using Non-MDS Linear Codes

We propose a private information retrieval (PIR) protocol for distributed storage systems with noncolluding nodes where data is stored using an arbitrary linear code. An expression for the PIR rate, i.e., the ratio of the amount of retrieved data per unit of downloaded data, is derived, and a necessary and a sufficient condition for codes to achieve the maximum distance separable (MDS) PIR capacity are given. The necessary condition is based on the generalized Hamming weights of the storage code, while the sufficient condition is based on code automorphisms. We show that cyclic codes and Reed-Muller codes satisfy the sufficient condition and are thus MDS-PIR capacity-achieving.Comment: To be presented at 2018 IEEE International Symposium on Information Theory (ISIT). arXiv admin note: substantial text overlap with arXiv:1712.0389

Asymmetry Helps: Improved Private Information Retrieval Protocols for Distributed Storage

We consider private information retrieval (PIR) for distributed storage systems (DSSs) with noncolluding nodes where data is stored using a non maximum distance separable (MDS) linear code. It was recently shown that if data is stored using a particular class of non-MDS linear codes, the MDS-PIR capacity, i.e., the maximum possible PIR rate for MDS-coded DSSs, can be achieved. For this class of codes, we prove that the PIR capacity is indeed equal to the MDS-PIR capacity, giving the first family of non-MDS codes for which the PIR capacity is known. For other codes, we provide asymmetric PIR protocols that achieve a strictly larger PIR rate compared to existing symmetric PIR protocols.Comment: To be presented at 2018 IEEE Information Theory Workshop (ITW'18). See arXiv:1808.09018 for its extended versio

Local Reconstruction Codes: A Class of MDS-PIR Capacity-Achieving Codes

We prove that a class of distance-optimal local reconstruction codes (LRCs), an important family of repair-efficient codes for distributed storage systems, achieve the maximum distance separable private information retrieval capacity for the case of noncolluding nodes. This particular class of codes includes Pyramid codes and other LRCs proposed in the literature.Comment: The contents of this manuscript is extracted from arXiv:1712.03898, and will be presented at the IEEE Information Theory Workshop (ITW), 201

Analysis of 10086 Microarray Gene Expression Data Uncovers Genes that Subclassify Breast Cancer Intrinsic Subtypes

Breast cancer is a complex disease comprising molecularly distinct subtypes. The prognosis and treatment differ between subtypes; thus, it is important to distinguish one subtype from another. In this chapter, we make use of high-throughput microarray dataset to perform breast cancer subtyping of 10086 samples. Aside from the four major subtypes, that is, Basal-like, HER2-enriched, luminal A, and luminal B, we defined a normal-like subtype that has a gene expression profile similar to that found in normal and adjacent normal breast samples. Also, a group of luminal B-like samples with better prognosis was distinguished from the high-risk luminal B breast cancer. We additionally identified 33 surface-protein encoding genes whose gene expression profiles were associated with survival outcomes. We believe these genes are potential therapeutic targets and diagnostic biomarkers for breast cancer

Protein domain repetition is enriched in Streptococcal cell-surface proteins

AbstractTandem repetition of domain in protein sequence occurs in all three domains of life. It creates protein diversity and adds functional complexity in organisms. In this work, we analyzed 52 streptococcal genomes and found 3748 proteins contained domain repeats. Proteins not harboring domain repeats are significantly enriched in cytoplasm, whereas proteins with domain repeats are significantly enriched in cytoplasmic membrane, cell wall and extracellular locations. Domain repetition occurs most frequently in S. pneumoniae and least in S. thermophilus and S. pyogenes. DUF1542 is the highest repeated domain in a single protein, followed by Rib, CW_binding_1, G5 and HemolysinCabind. 3D structures of 24 repeat-containing proteins were predicted to investigate the structural and functional effect of domain repetition. Several repeat-containing streptococcal cell surface proteins are known to be virulence-associated. Surface-associated tandem domain-containing proteins without experimental functional characterization may be potentially involved in the pathogenesis of streptococci and deserve further investigation