Unintended consequences on gender diversity of high-tech growth and labor market polarization

There has been considerable media coverage highlighting the lack of gender diversity in Silicon Valley, stressing the relatively low participation of women in the high-tech economy. Austin offers a unique case for testing whether similar gender issues characterized other high-tech regions because the city has historically benefited from the expansion of Silicon Valley’s large high-tech firms since the 1980s. The gender-biased business practices identified in Silicon Valley firms may have been transferred to their branch plants in Austin. Our analysis shows women’s losses in middle-skill occupation employment shares were concentrated in the low-tech industry and were partially offset by job share gains in high-skill occupations in the same sector between 1980 and 2015. Men’s losses in middle-skill occupation job share were also mainly concentrated in the low-tech sector but were partially offset by employment share gains in high-skill occupations only in the high-tech industry during this period. Women made large gains in relative real median wages only in high-skill occupations in the high-tech industry while their relative real median wages in other skill occupations and in the low-tech industry stagnated around zero during this period. Men’s gains in relative median wages were also concentrated only in the high-tech industry but were less than half of women’s and were negative (between ?10 and ?21 percent) in other occupations in the high-tech industry and across all occupations in the low-tech industry. As noted in previous studies, the impact of job polarization is not well understood across sectors and gender. This study finds the high-tech industry in Austin has had unintended consequences in terms of job polarization across gender, providing relatively fewer job opportunities in high-skill occupations to women than men but offering much higher gains in relative real median wages to women than men. Males also found relatively more job opportunities in high-skill occupations in the high-tech industry than women but experienced only half of women’s gains in relative median wages in this industry between 1980 and 2015.     

A relevance feedback mechanism for cluster-based retrieval

Contextual document clustering is a novel approach which uses information theoretic measures to cluster semantically related documents bound together by an implicit set of concepts or themes of narrow specificity. It facilitates cluster-based retrieval by assessing the similarity between a query and the cluster themes’ probability distribution. In this paper, we assess a relevance feedback mechanism, based on query refinement, that modifies the query’s probability distribution using a small number of documents that have been judged relevant to the query. We demonstrate that by providing only one relevance judgment, a performance improvement of 33% was obtained.     

The information seeking behaviour of the users of digital scholarly journals

The article employs deep log analysis (DLA) techniques, a more sophisticated form of transaction log analysis, to demonstrate what usage data can disclose about information seeking behaviour of virtual scholars – academics, and researchers. DLA works with the raw server log data, not the processed, pre-defined and selective data provided by journal publishers. It can generate types of analysis that are not generally available via proprietary web logging software because the software filters out relevant data and makes unhelpful assumptions about the meaning of the data. DLA also enables usage data to be associated with search/navigational and/or user demographic data, hence the name ‘deep’. In this connection the usage of two digital journal libraries, those of EmeraldInsight, and Blackwell Synergy are investigated. The information seeking behaviour of nearly three million users is analyzed in respect to the extent to which they penetrate the site, the number of visits made, as well as the type of items and content they view. The users are broken down by occupation, place of work, type of subscriber (“Big Deal”, non-subscriber, etc.), geographical location, type of university (old and new), referrer link used, and number of items viewed in a session.     

新生代员工核心自我评价与工作投入的关系:有调节的中介模型

采用核心自我评价量表、工作投入量表、心理授权量表和不匹配感知量表对16家企业447名新生代员工进行调查,通过层级回归分析新生代员工核心自我评价与工作投入的关系,以及考察心理授权与过度教育在此关系中发挥的作用。结果表明:(1)新生代员工核心自我评价对工作投入有显著正向影响;(2)心理授权在核心自我评价和工作投入关系中有着部分中介效应;(3)过度教育对心理授权中介效应的调节作用成立,对过度教育的高感知不仅削弱了核心自我评价与心理授权的正向关系,也进而弱化了心理授权对工作投入的积极作用。     

Surface superconductivity in the type II Weyl semimetal TaIrTe4

The search for unconventional superconductivity in Weyl semimetal materials is currently an exciting pursuit, since such superconducting phases could potentially be topologically non-trivial and host exotic Majorana modes. The layered material TaIrTe₄ is a newly predicted time-reversal invariant type II Weyl semimetal with the minimum number of Weyl points. Here, we report the discovery of surface superconductivity in Weyl semimetal TaIrTe₄. Our scanning tunneling microscopy/spectroscopy (STM/STS) visualizes Fermi arc surface states of TaIrTe₄ that are consistent with the previous angle-resolved photoemission spectroscopy results. By a systematic study based on STS at ultralow temperature, we observe uniform superconducting gaps on the sample surface. The superconductivity is further confirmed by electrical transport measurements at ultralow temperature, with an onset transition temperature (T_c) up to 1.54 K being observed. The normalized upper critical field h*(T/T_c) behavior and the stability of the superconductivity against the ferromagnet indicate that the discovered superconductivity is unconventional with the p-wave pairing. The systematic STS, and thickness- and angular-dependent transport measurements reveal that the detected superconductivity is quasi-1D and occurs in the surface states. The discovery of the surface superconductivity in TaIrTe₄ provides a new novel platform to explore topological superconductivity and Majorana modes.     

Convergent genomic signatures of high-altitude adaptation among domestic mammals

Abundant and diverse domestic mammals living on the Tibetan Plateau provide useful materials for investigating adaptive evolution and genetic convergence. Here, we used 327 genomes from horses, sheep, goats, cattle, pigs and dogs living at both high and low altitudes, including 73 genomes generated for this study, to disentangle the genetic mechanisms underlying local adaptation of domestic mammals. Although molecular convergence is comparatively rare at the DNA sequence level, we found convergent signature of positive selection at the gene level, particularly the EPAS1 gene in these Tibetan domestic mammals. We also reported a potential function in response to hypoxia for the gene C10orf67, which underwent positive selection in three of the domestic mammals. Our data provide an insight into adaptive evolution of high-altitude domestic mammals, and should facilitate the search for additional novel genes involved in the hypoxia response pathway.     

Learning,innovation and firm performance: knowledge management in small firms

This study aims to examine the relationships between managerial learning as a facet of knowledge absorption (KA), firm innovation as a facet of knowledge exploitation (KE), and performance of small firms (i.e., firms with fewer than 50 employees). It builds on the knowledge-based view of the firm and the upper echelons theory to describe the effects of KA on KE, and that of KE on firm performance, in the small-firm context. Using survey data of 1441 small firms in New Zealand, the study applies a partial least squares approach to structural equation modelling to test the main hypotheses of the study. The main findings show the positive and significant effects of three types of managerial learning, namely, practice-based, proximal, and distal learning, on innovation and on innovation in firm performance. However, the curvilinear relationships suggest rather that the effects are finite and, potentially, confounded by factors unaccounted for in the models.