Birthplace Effects on the Development of Female Athletic Talent

This study examined the extent to which an athlete's place of birth can influence the likelihood of playing professional sport. Information regarding the birthplace of all American female athletes in the Ladies Professional Golf Association and Women's United Soccer Association was gathered from official league websites. Monte Carlo simulations were used to determine if the birthplace of these professional athletes differed in any systematic way from official census population distributions. Odds-ratios were determined for cities within specific population ranges to ascertain if the likelihood of playing professional sport was influenced in any systematic way by city size. The analyses revealed that female professional soccer players born in cities of less than 1,000,000 were over-represented, as were female professional golfers born in cities of less than 250,000. Results are consistent with those of male professional athletes in suggesting that areas of lower population provide conditions more conducive to the development of expertise than do larger city environments.

When “Where” is More Important Than “When”: Birthplace and Birthdate Effects On The Achievement Of Sporting Expertise

In this study, we assessed whether contextual factors related to where or when an athlete is born influence their likelihood of playing professional sport. The birthplace and birth month of all American players in the National Hockey League, National Basketball Association, Major League Baseball, and Professional Golfer's Association, and all Canadian players in the National Hockey League were collected from official websites. Monte Carlo simulations were used to verify if the birthplace of these professional athletes deviated in any systematic way from the official census population distribution, and chi-square analyses were conducted to determine whether the players' birth months were evenly distributed throughout the year. Results showed a birthplace bias towards smaller cities, with professional athletes being over-represented in cities of less than 500,000 and under-represented in cities of 500,000 and over. A birth month/relative age effect (in the form of a distinct bias towards elite athletes being relatively older than their peers) was found for hockey and baseball but not for basketball and golf. Comparative analyses suggested that contextual factors associated with place of birth contribute more influentially to the achievement of an elite level of sport performance than does relative age and that these factors are essentially independent in their influences on expertise development.

Assisting End-users in Filling Out Web Services

With the quick advance of web service technologies, end-users can conduct various on-line tasks, such as shopping on-line. Usually, end-users compose a set of services to accomplish a task, and need to enter values to services to invoke the composite services. Quite often, users re-visit websites and use services to perform re-occurring tasks. The users are required to enter the same information into various web services to accomplish such re-occurring tasks. However, repetitively typing the same information into services is a tedious job for end-users. It can negatively impact user experience when an end-user needs to type the re-occurring information repetitively into web services. Recent studies have proposed several approaches to help users fill in values to services automatically. However, prior studies mainly suffer the following drawbacks: (1) limited support of collecting and analyzing user inputs; (2) poor accuracy of filling values to services; (3) not designed for service composition. To overcome the aforementioned drawbacks, we need maximize the reuse of previous user inputs across services and end-users. In this thesis, we introduce our approaches that prevent end-users from entering the same information into repetitive on-line tasks. More specifically, we improve the process of filling out services in the following 4 aspects: First, we investigate the characteristics of input parameters. We propose an ontology-based approach to automatically categorize parameters and fill values to the categorized input parameters. Second, we propose a comprehensive framework that leverages user contexts and usage patterns into the process of filling values to services. Third, we propose an approach for maximizing the value propagation among services and end-users by linking a set of semantically related parameters together and similar end-users. Last, we propose a ranking-based framework that ranks a list of previous user inputs for an input parameter to save a user from unnecessary data entries. Our framework learns and analyzes interactions of user inputs and input parameters to rank user inputs for input parameters under different contexts.