Women's consumption of men's professional sport in Canada: Evidence of the ‘feminization’ of sports fandom and women as omnivorous sports consumers?

2021 ◽  
pp. 101269022110264
Author(s):  
Adam Gemar ◽  
Stacey Pope
Keyword(s):  
Large Scale ◽  
Quantitative Methods ◽  
Latent Class ◽  
Cultural Barriers ◽  
Sports Fans ◽  
Gender Gaps ◽  
Potential Growth ◽  
Sports Fandom ◽  
Social Settings ◽  
Time Period

Women sports fans have been substantially understudied compared to their male counterparts. While a growing number of studies seek to redress this, there remains a stark absence of quantitative approaches that would allow investigations regarding patterns of women’s sporting consumption and historical trends in the potential growth of this fandom. Using large-scale survey data from Canada from 1990 through to 2015, and employing quantitative methods of latent class and regression analysis, this study seeks to redress these issues by testing the ‘feminization’ thesis of increased women’s sporting fandom over the past three decades. In addition, we consider whether women’s fandom has become increasingly ‘omnivorous’ over this time period and the nature of this consumption today. Results show support for the feminization thesis. These findings are significant as through the use of quantitative methodologies we evidence the narrowing gender gaps in professional sports following between men and women, and women’s increasingly omnivorous consumption of sports. However, we find substantial gender gaps and inequalities in omnivorism by which the evidence suggests increased socio-economic and cultural barriers to omnivorous consumption of sport for women. We suggest that these women omnivores may be able to utilize their sporting knowledge in an instrumental way for benefits in various social settings, especially workplaces. It is hoped that this article will pave the way for further quantitative studies on women sports fans across different contexts.

scholarly journals Classification of Recreation Opportunity Spectrum Using Night Lights for Evidence of Humans and POI Data for Social Setting

2021 ◽  
Vol 13 (14) ◽  
pp. 7782
Author(s):  
Wenjing Zeng ◽  
Yongde Zhong ◽  
Dali Li ◽  
Jinyang Deng
Keyword(s):  
Large Scale ◽  
Regional Scale ◽  
Hunan Province ◽  
Social Settings ◽  
Recreation Opportunity Spectrum ◽  
City District ◽  
Night Lights ◽  
Recreational Resources ◽  
Metropolitan Counties ◽  
Land Types

The recreation opportunity spectrum (ROS) has been widely recognized as an effective tool for the inventory and planning of outdoor recreational resources. However, its applications have been primarily focused on forest-dominated settings with few studies being conducted on all land types at a regional scale. The creation of a ROS is based on physical, social, and managerial settings, with the physical setting being measured by three criteria: remoteness, size, and evidence of humans. One challenge to extending the ROS to all land types on a large scale is the difficulty of quantifying the evidence of humans and social settings. Thus, this study, for the first time, developed an innovative approach that used night lights as a proxy for evidence of humans and points of interest (POI) for social settings to generate an automatic ROS for Hunan Province using Geographic Information System (GIS) spatial analysis. The whole province was classified as primitive (2.51%), semi-primitive non-motorized (21.33%), semi-primitive motorized (38.60%), semi-developed natural (30.99%), developed natural (5.61%), and highly developed (0.96%), which was further divided into three subclasses: large-natural (0.63%), small natural (0.27%), and facilities (0.06%). In order to implement the management and utilization of natural recreational resources in Hunan Province at the county (city, district) level, the province’s 122 counties (cities, districts) were categorized into five levels based on the ROS factor dominance calculated at the county and provincial levels. These five levels include key natural recreational counties (cities, districts), general natural recreational counties (cities, districts), rural counties (cities, districts), general metropolitan counties (cities, districts), and key metropolitan counties (cities, districts), with the corresponding numbers being 8, 21, 50, 24, and 19, respectively.

scholarly journals Local Differential Privacy for Evolving Data

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Matthew Joseph ◽  
Aaron Roth ◽  
Jonathan Ullman ◽  
Bo Waggoner
Keyword(s):  
Large Scale ◽  
Differential Privacy ◽  
Statistical Information ◽  
Underlying Distribution ◽  
Specific Distribution ◽  
Time Period ◽  
Long Time ◽  
Heavy Hitter ◽  
Single Use ◽  
A New Technique

There are now several large scale deployments of differential privacy used to collect statistical information about users. However, these deployments periodically recollect the data and recompute the statistics using algorithms designed for a single use. As a result, these systems do not provide meaningful privacy guarantees over long time scales. Moreover, existing techniques to mitigate this effect do not apply in the “local model” of differential privacy that these systems use. In this paper, we introduce a new technique for local differential privacy that makes it possible to maintain up-to-date statistics over time, with privacy guarantees that degrade only in the number of changes in the underlying distribution rather than the number of collection periods. We use our technique for tracking a changing statistic in the setting where users are partitioned into an unknown collection of groups, and at every time period each user draws a single bit from a common (but changing) group-specific distribution. We also provide an application to frequency and heavy-hitter estimation.

scholarly journals Present and LGM permafrost from climate simulations: contribution of statistical downscaling

2010 ◽  
Vol 4 (4) ◽  
pp. 2233-2275 ◽  
Author(s):  
G. Levavasseur ◽  
M. Vrac ◽  
D. M. Roche ◽  
D. Paillard ◽  
A. Martin ◽  
...  
Keyword(s):  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Models ◽  
Multinomial Logistic Regression ◽  
Generalized Additive Models ◽  
Regional Scale ◽  
Surface Air Temperature ◽  
Additive Models ◽  
Simple Relationship ◽  
Time Period

Abstract. We quantify the agreement between permafrost distributions from PMIP2 (Paleoclimate Modeling Intercomparison Project) climate models and permafrost data. We evaluate the ability of several climate models to represent permafrost and assess the inter-variability between them. Studying an heterogeneous variable such as permafrost implies to conduct analysis at a smaller spatial scale compared with climate models resolution. Our approach consists in applying statistical downscaling methods (SDMs) on large- or regional-scale atmospheric variables provided by climate models, leading to local permafrost modelling. Among the SDMs, we first choose a transfer function approach based on Generalized Additive Models (GAMs) to produce high-resolution climatology of surface air temperature (SAT). Then, we define permafrost distribution over Eurasia by SAT conditions. In a first validation step on present climate (CTRL period), GAM shows some limitations with non-systemic improvements in comparison with the large-scale fields. So, we develop an alternative method of statistical downscaling based on a stochastic generator approach through a Multinomial Logistic Regression (MLR), which directly models the probabilities of local permafrost indices. The obtained permafrost distributions appear in a better agreement with data. In both cases, the provided local information reduces the inter-variability between climate models. Nevertheless, this also proves that a simple relationship between permafrost and the SAT only is not always sufficient to represent local permafrost. Finally, we apply each method on a very different climate, the Last Glacial Maximum (LGM) time period, in order to quantify the ability of climate models to represent LGM permafrost. Our SDMs do not significantly improve permafrost distribution and do not reduce the inter-variability between climate models, at this period. We show that LGM permafrost distribution from climate models strongly depends on large-scale SAT. The differences with LGM data, larger than in the CTRL period, reduce the contribution of downscaling and depend on several factors deserving further studies.

scholarly journals How public perceptions of social distancing evolved over a critical time period: communication lessons learnt from the American state of Wisconsin

2020 ◽  
Vol 19 (05) ◽  
pp. A11
Author(s):  
Kaiping Chen ◽  
Luye Bao ◽  
Anqi Shao ◽  
Pauline Ho ◽  
Shiyu Yang ◽  
...  
Keyword(s):  
Public Health ◽  
Computational Methods ◽  
Large Scale ◽  
Critical Time ◽  
Effective Communication ◽  
Public Perceptions ◽  
Social Distancing ◽  
Time Period ◽  
Large Scale Survey ◽  
Main Barrier

Understanding how individuals perceive the barriers and benefits of precautionary actions is key for effective communication about public health crises, such as the COVID-19 outbreak. This study used innovative computational methods to analyze 30,000 open-ended responses from a large-scale survey to track how Wisconsin (U.S.A.) residents' perceptions of the benefits of and barriers to performing social distancing evolved over a critical time period (March 19th to April 1st, 2020). Initially, the main barrier was practical related, however, individuals later perceived more multifaceted barriers to social distancing. Communication about COVID-19 should be dynamic and evolve to address people's experiences and needs overtime.

scholarly journals Measuring the value of a digital supplemental resource

2021 ◽  
Vol 45 (4) ◽  
pp. 685-693
Author(s):  
Yvonne M. Baptiste ◽  
Samuel Abramovich ◽  
Cherylea J. Browne
Keyword(s):  
Factor Analysis ◽  
Science Education ◽  
Construct Validity ◽  
Student Perceptions ◽  
Large Scale ◽  
Quantitative Methods ◽  
Student Perception ◽  
Digital Learning ◽  
Internal Reliability ◽  
Traditional Component

Supplemental resources in science education are made available to students based on the belief that they will improve course-based student learning. This belief is ubiquitous, with supplemental resources being a traditional component of physiology education. In addition, the recent large-scale transition to remote learning caused by the Covid-19 pandemic suggests an increased relevance and necessity of digital versions of supplemental resources. However, the use of a supplemental resource is entirely dependent on whether students view it as beneficial. If students in a specific course do not perceive a supplemental resource as useful, there is little reason to believe the resources will be used and are worthy of investment. Consequently, measurement of student perception regarding the effectiveness of any digital learning tool is essential for educators and institutions in order to prioritize resources and make meaningful recommendations to students. In this study, a survey was used to determine student perceptions of a digital, supplemental resource. Quantitative methods, including exploratory factor analysis, were performed on data collected from the survey to examine the dimensionality and functionality of this survey. The findings from this study were used to devise an improved, standardized (i.e., reliable and valid) survey that can be used and adapted by physi3ology researchers and educators to determine student perception of a digital supplemental resource. The survey, with known construct validity and internal reliability, can provide useful information for administrators, instructors, and designers of digital supplemental resources.

scholarly journals Discovering Latent Class Labels for Multi-Label Learning

2020 ◽  
Author(s):  
Jun Huang ◽  
Linchuan Xu ◽  
Jing Wang ◽  
Lei Feng ◽  
Kenji Yamanishi
Keyword(s):  
Large Scale ◽  
Latent Class ◽  
Training Data ◽  
Data Sets ◽  
Robust Learning ◽  
Large Scale Data ◽  
Novel Approach ◽  
Fixed Set ◽  
Class Labels ◽  
Scale Data

Existing multi-label learning (MLL) approaches mainly assume all the labels are observed and construct classification models with a fixed set of target labels (known labels). However, in some real applications, multiple latent labels may exist outside this set and hide in the data, especially for large-scale data sets. Discovering and exploring the latent labels hidden in the data may not only find interesting knowledge but also help us to build a more robust learning model. In this paper, a novel approach named DLCL (i.e., Discovering Latent Class Labels for MLL) is proposed which can not only discover the latent labels in the training data but also predict new instances with the latent and known labels simultaneously. Extensive experiments show a competitive performance of DLCL against other state-of-the-art MLL approaches.

SEARCH FOR NEW METHODOLOGICAL APPROACHES AND METHODS IN RISK MANAGEMENT

2021 ◽  
Vol 54 (2) ◽  
pp. 35-47
Author(s):  
Svetlana N. Dvoryatkina ◽  
◽  
Arseny M. Lopukhin ◽  
Keyword(s):  
Risk Management ◽  
Large Scale ◽  
Quantitative Methods ◽  
Knowledge Bases ◽  
Fractal Model ◽  
Educational Process ◽  
Machine Learning Algorithms ◽  
Risk Modeling ◽  
Negative Consequences ◽  
Fractal Approach

The study actualized the complex and large-scale problem of adapting the theory of risk man-agement for the education system. A comprehensive analysis of domestic and international stud-ies revealed the lack of a theoretical framework, a general methodological vision of the problem of riskiness and risk-taking in the educational sphere. While effective management of education-al activities, ensuring the development of the competitiveness of the individual in the labor mar-ket and its potential for active participation in the life of society is possible on the basis of the modern paradigm of risk management, integrating achievements in pedagogical, economic, mathematical and computer sciences. A new methodology in the study is the fractal approach, which defines the idea of quantitative and qualitative analysis and assessment of the risk of non-formation of professional competencies, complex educational and cognitive constructs of subject activity. The fractal model of assessing the formation of knowledge and competencies, its risk landscape, taking into account the subject and cognitive divergence, will ensure the effective-ness of the structure of knowledge storage in the educational process, minimizing the time for building space and engineering knowledge bases, and the depth of solving the problem of pre-dicting educational risks. New methods of risk modeling based on machine learning algorithms and factor analysis, methods for constructing neural integrators, quantitative methods with and without taking into account the probability distribution will ensure the accuracy and speed of risk assessment and prediction, will allow one to identify new patterns of risk activity and further ways to develop the theory of risk. The presented effective strategies and innovative tools will solve the problem of minimizing unplanned chaos, the cascade of negative consequences of risky situations, including the COVID-19 epidemic.

Latent class analysis and individuals' preferences mapping: the new consumption orientations and perspectives for craft beer in North-West Italy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stefano Massaglia ◽  
Valentina Maria Merlino ◽  
Simone Blanc ◽  
Aurora Bargetto ◽  
Danielle Borra
Keyword(s):  
Latent Class Analysis ◽  
Large Scale ◽  
Latent Class ◽  
Consumer Preferences ◽  
Demographic Characteristics ◽  
Class Analysis ◽  
Content Type ◽  
North West ◽  
Craft Beer ◽  
Definition Of

PurposeIn Italy, the craft beer (CB) market has undergone a trend of exponential growth in recent years, showing, at the same time, differences among different geographical areas. This research aimed to define the consumer preferences towards different CB attributes by involving a sample of individuals from Piedmont (from North-West Italy). Furthermore, the experimentation was designed to distinguish heterogeneous individuals' consumption profiles each characterised by different CB preferences, drinking habits and socio-demographic characteristics.Design/methodology/approachThe exploration of individuals' preferences towards 12 CB quality attributes was made throughout a choice experiment based on the Best-Worst Scaling (BWS) methodology approach. In addition, the BWS results were employed in the latent class analysis to identify the best sample segmentation in relation to attributes preferences.FindingsThe “Brand knowledge”, “I have already tried it” were the most important attributes for CB choice. On the contrary, the “Type of packaging” and “Price” were the least important for CB choice. The “Loyal”, “Attentive to quality composition” and “Territorial brand” clusters were defined in function of CB consumers preferences and described in terms of individuals consumption habits and socio-demographic characteristics.Originality/valueThe BWS methodology allowed the definition of a preference index for each selected CB attributes. These indications could have concrete importance on production and marketing choices in an increasingly extended and globalised market, also at large-scale distribution level. Furthermore, the definition of different consumption profiles allowed to highlight the heterogeneity of consumption (preferences and habits) towards CB.

Sport Fan Consumption

2020 ◽  
pp. 149-170 ◽  
Author(s):  
Lauren Michele Johnson ◽  
Wen-Hao Winston Chou ◽  
Brandon Mastromartino ◽  
James Jianhui Zhang
Keyword(s):  
Cultural Heritage ◽  
Sports Fans ◽  
Sports Teams ◽  
Developmental Trends ◽  
Contemporary Research ◽  
Sports Fandom ◽  
Sport Fan ◽  
Or Team

Sports fans are individuals who are interested in and follow one or more sports, teams, and/or athletes. These fans reinforce their identity as a fan by engaging in supportive and repetitive consumption behaviors that relate to the sport or team they are so passionate about. This chapter will provide an overview of the history and cultural heritage of sports fandom, discuss the significance and functions of fandom, underline what motivates individuals to consume sports, examine the consequences and results of fandom, and highlight contemporary research and developmental trends. This chapter would allow for a good understanding of where research on sports fandom is headed and the important issues affecting sports fans.

Research Challenges and Opportunities in Conducting Quantitative Studies on Large-Scale Agile Methodology

2020 ◽  
Vol 31 (2) ◽  
pp. 64-73
Author(s):  
Dinesh Batra
Keyword(s):  
Large Scale ◽  
Empirical Literature ◽  
Adoption Studies ◽  
Agile Methodology ◽  
Quantitative Studies ◽  
Balanced Approach ◽  
Research Challenges ◽  
Time Period ◽  
Dependent Variables ◽  
Challenges And Opportunities

This research note suggests five research challenges when conducting quantitative studies on large-scale agile methodology (LSAM). First, the LSAM empirical literature, which is mainly characterized by qualitative studies primarily focusing on coordination issues, provides limited background. Second, the notion of “large” in LSAM needs to be clarified because the existing research seems to have focused on “very large” or outlier projects. Third, the popular LSAM methods suggest broad and general maxims that may result in difficulty in operationalizing dependent variables, especially in innovation adoption studies. Fourth, the researcher may get overwhelmed when selecting independent variables from the plethora of suggested constructs. Finally, some of the problems associated with large-scale agile are mostly challenges of using conventional agile during a time-period when LSAM had not formally emerged. Researchers should take a balanced approach considering both benefits and challenges of using LSAM and focusing on project-level dependent measures such as success and acceptance.

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