56 research outputs found

    Competent Men and Warm Women: Gender Stereotypes and Backlash in Image Search Results

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    There is much concern about algorithms that underlie information services and the view of the world they present. We develop a novel method for examining the content and strength of gender stereotypes in image search, inspired by the trait adjective checklist method. We compare the gender distribution in photos retrieved by Bing for the query “person” and for queries based on 68 character traits (e.g., “intelligent person”) in four regional markets. Photos of men are more often retrieved for “person,” as compared to women. As predicted, photos of women are more often retrieved for warm traits (e.g., “emotional”) whereas agentic traits (e.g., “rational”) are represented by photos of men. A backlash effect, where stereotype-incongruent individuals are penalized, is observed. However, backlash is more prevalent for “competent women” than “warm men.” Results underline the need to understand how and why biases enter search algorithms and at which stages of the engineering proces

    Evaluation: Thinking Outside the (Search) Box

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    Evaluation of IR systems has typically focused on the system and specifically assessing the quality of a ranked list of results with respect to a query. However, IR functionality is typically just one component amongst many that are used to help support users' wider information seeking activities. Many systems that include a search box also provide features, such as faceted lists, subject hierarchies, visualizations and recommendations to help users find information. In this paper I discuss experiences gained from developing a system to support exploration and discovery in digital cultural heritage. In particular I focus on the development of system components to support search and navigation and how the different components were evaluated within the development life-cycle of the project. The importance of taking a holistic approach to evaluation, as well as utilising evaluation approaches from domains other than IR, is emphasized. In short, we need to be thinking outside the (search) box when it comes to evaluation in IR

    How the information use environment influences search activities: a case of English primary schools

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    Purpose The information use environment (IUE) – the context within which the search activity takes place – is critical to understanding the search process as this will affect how the value of information is determined. The purpose of this paper is to investigate what factors influence search in English primary schools (children aged 4–11) and how information found is subsequently used. Design/methodology/approach Ten teachers, selected using maximal variation sampling, describe search-related activities within the classroom. The resulting interview data were analysed thematically for the influence of the environment on search and different information uses. The findings were then validated against three classroom observations. Findings 12 categories of information use were identified, and 5 aspects of the environment (the national curriculum, best practice, different skills of children and teachers, keeping children safe, and limited time and resource) combine to influence and shape search in this setting. Research limitations/implications Findings support the argument that it is the IUE that is the key influence of search activity. What makes children a distinct user group is linked to the environment within which they use information rather than age, as advocated in previous studies. Practical implications The features of search systems and practical guidance for teachers and children should be designed to support information use within the IUE. Originality/value As far as the authors are aware, this is the first study to consider the influence of the IUE on how search is enacted within primary schools

    Investigating the usage of IoT-based smart parking services in the Borough of Westminster

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    Smart Parking schemes cannot succeed without the engagement and support of the drivers who may benefit from their use. This study investigates engagement with a Smart Parking service in the London Borough of Westminster. Factors likely to influence the use of Smart Parking services were identified from a literature review and incorporated into an explanatory model comprising 9 factors connected by 16 hypotheses. To test the model, residents of Westminster and visitors to the area were surveyed, resulting in a total of 212 valid responses. The responses were used to test a structural equation model, using confirmatory factor analysis. The results of the analysis indicated that Awareness of the scheme; Perceived Ease of Use; Perceived Usefulness; Cost saving; Perceived Privacy and Perceived Security all had a direct impact on Usage, with Awareness being the most influential factor. The results also highlighted the fact that, despite efforts by Westminster Council to publicise the scheme, 74% of respondents had little awareness of it, suggesting the need for improved publicity

    Integrating FATE/critical data studies into data science curricula : where are we going and how do we get there?

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    There have been multiple calls for integrating topics related to fairness, accountability, transparency, ethics (FATE) and social justice into Data Science curricula, but little exploration of how this might work in practice. This paper presents the findings of a collaborative auto-ethnography (CAE) engaged in by a MSc Data Science teaching team based at University of Sheffield (UK) Information School where FATE/Critical Data Studies (CDS) topics have been a core part of the curriculum since 2015/16. In this paper, we adopt the CAE approach to reflect on our experiences of working at the intersection of disciplines, and our progress and future plans for integrating FATE/CDS into the curriculum. We identify a series of challenges for deeper FATE/CDS integration related to our own competencies and the wider socio-material context of Higher Education in the UK. We conclude with recommendations for ourselves and the wider FATE/CDS orientated Data Science community

    Observation of a new Xi(b) baryon

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    The first observation of a new b baryon via its strong decay into Xi(b)^- pi^+ (plus charge conjugates) is reported. The measurement uses a data sample of pp collisions at sqrt(s) = 7 TeV collected by the CMS experiment at the LHC, corresponding to an integrated luminosity of 5.3 inverse femtobarns. The known Xi(b)^- baryon is reconstructed via the decay chain Xi(b)^- to J/psi Xi^- to mu^+ mu^- Lambda^0 pi^-, with Lambda^0 to p pi^-. A peak is observed in the distribution of the difference between the mass of the Xi(b)^- pi^+ system and the sum of the masses of the Xi(b)^- and pi^+, with a significance exceeding five standard deviations. The mass difference of the peak is 14.84 +/- 0.74 (stat.) +/- 0.28 (syst.) MeV. The new state most likely corresponds to the J^P=3/2^+ companion of the Xi(b).Comment: Submitted to Physical Review Letter

    Measurement of the charge ratio of atmospheric muons with the CMS detector

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    This is the pre-print version of this Article. The official published version can be accessed from the link below - Copyright @ 2010 ElsevierWe present a measurement of the ratio of positive to negative muon fluxes from cosmic ray interactions in the atmosphere, using data collected by the CMS detector both at ground level and in the underground experimental cavern at the CERN LHC. Muons were detected in the momentum range from 5 GeV/c to 1 TeV/c. The surface flux ratio is measured to be 1.2766 \pm 0.0032(stat.) \pm 0.0032 (syst.), independent of the muon momentum, below 100 GeV/c. This is the most precise measurement to date. At higher momenta the data are consistent with an increase of the charge ratio, in agreement with cosmic ray shower models and compatible with previous measurements by deep-underground experiments
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