The exercise leader's gender and physique salience : effects on self-presentational concerns in an exercise context

Self-presentation is the process by which individuals attempt to monitor and control how others perceive and evaluate them (Leary, 1992; Leary & Kowalski, 1990). Self-presentational concerns have been shown to influence a number of exercise-related behaviours, cognitions, and affective responses to exercise (e.g., social anxiety). Social anxiety occurs when an individual wants to create a specific impression on others, but is unsure (s)he will be successful (Leary & Kowalski, 1995). Social physique anxiety (SPA) is a specific form of social anxiety related the evaluation of one's body (Hart, Leary, & Rejeski, 1989). Both social anxiety and SPA may act as deterrents to exercise (Lantz, Hardy, & Ainsworth, 1997; Leary, 1992), so it is important to examine factors that may influence social anxiety and SPA; one such factor is self-presentational efficacy (SPE). SPE is one's confidence in successfully making desired impressions on others (Leary & Atherton, 1986) and has been associated with social anxiety and SPA (Leary & Kowalski, 1995; Gammage, Martin Ginis, & Hall, 2004). Several aspects of the exercise environment, such as the presence of mirrors, clothing, and the exercise leader or other participant characteristics, may be manipulated to influence self-presentational concerns (e.g., Gammage, Martin Ginis et aI., 2004; Martin & Fox, 2001; Martin Ginis, Prapavessis, & Haase, 2005). Given that the exercise leader has been recognized as one of the most important influences in the group exercise context (Franklin, 1988), it is important to further examine how the leader may impact self-presentational concerns. The present study examined the impact of the exercise leader's gender and physique salience (i.e., the extent to which the body was emphasized) on SPE, state social anxiety (SSA), and state social physique anxiety (SPA-S) of women in a live exercise class. Eighty-seven college-aged female non- or infrequent exercisers (i.e., exercised 2 or fewer times per week) participated in a group exercise class led by one of four leaders: a female whose physique was salient; a female whose physique was non-salient; a male whose physique was salient; or a male whose physique was non-salient. Participants completed measures of SPE, SSA, and SPA-S prior to and following completion of a 30- minute group exercise class. In addition, a measure of social comparison to the exercise leader and other participants with respect to attractiveness, skill, and fitness was completed by participants following the exercise class. A MANOV A was conducted to examine differences between groups on postexercise variables. Results indicated that there were no significant differences between groups on measures ofSPE, SSA, or SPA-S (allp's > .05). However, when all participants were collapsed into one group, a MANOV A showed a significant time effect (F(3, 81) = 19.45,p < .05, 1')2= .419). Follow-up ANOVAs indicated that post-exercise SPE increased significantly, while SSA and SPA-S decreased significantly (SPE: F(I, 83) = 30.87,p < .001,1')2 = .27; SSA: F(I,83) = 11.09,p < .001, 1')2 = .12; SPA-S: F (1,83) = 42.79,p < .001, 1')2 = .34). Further, results of a MANOVA revealed that participants who believed they were less fit than other group members (i.e., made negative social comparisons) reported significantly more post-exercise SSA and SP A-S than those who believed they were more fit than the other participants (i.e., made positive comparisons; SSA: F(2, 84) = 3.46, p < .05, 1')2 = .08; SPA-S: F(2, 84) = 5.69, p < .05, 1')2 = .12). These results may indicate that successfully completing an exercise class may serve as a source of SPE and lead to reduced social anxiety and SPA-S in this population. Alternatively, characteristics of the exercise leader may be less important than characteristics of the other participants. These results also suggest that the types of social comparisons made may influence self-presentational concerns in this sample. Future research should examine how the type of social comparison (i.e., negative or positive) made to the other group members may either generate or reduce anxiety. Also, factors that contribute to the types of social comparisons made with other exercisers should be examined. Implications for practice and research are discussed.

Evolutionary synthesis of stochastic gene network models using feature-based search spaces

A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.

Comparison of classification ability of hyperball algorithms to neural network and k-nearest neighbour algorithms

The main focus of this thesis is to evaluate and compare Hyperbalilearning algorithm (HBL) to other learning algorithms. In this work HBL is compared to feed forward artificial neural networks using back propagation learning, K-nearest neighbor and 103 algorithms. In order to evaluate the similarity of these algorithms, we carried out three experiments using nine benchmark data sets from UCI machine learning repository. The first experiment compares HBL to other algorithms when sample size of dataset is changing. The second experiment compares HBL to other algorithms when dimensionality of data changes. The last experiment compares HBL to other algorithms according to the level of agreement to data target values. Our observations in general showed, considering classification accuracy as a measure, HBL is performing as good as most ANn variants. Additionally, we also deduced that HBL.:s classification accuracy outperforms 103's and K-nearest neighbour's for the selected data sets.

Riffing on a Theme: Faculty Experiences With Service-Learning in a Food Security Research Network in Ontario

While service-learning is often said to be beneficial for all those involved—students, community members, higher education institutions, and faculty members—there are relatively few studies of the attraction to, and effect of, service-learning on faculty members. Existing studies have tended to use a survey design, and to be based in the United States. There is a lack of information on faculty experiences with service-learning in Ontario or Canada. This qualitative case study of faculty experiences with service-learning was framed through an Appreciative Inquiry social constructionist approach. The data were drawn from interviews with 18 faculty members who belong to a Food Security Research Network (FSRN) at a university in northern Ontario, reports submitted by the network, and personal observation of a selection of network-related events. This dissertation study revealed how involvement with service-learning created opportunities for faculty learning and growth. The focus on food security and a commitment to the sustainability of local food production was found to be an ongoing attraction to service-learning and a means to engage in and integrate research and teaching on matters of personal and professional importance to these faculty members. The dissertation concludes with a discussion of the FSRN’s model and the perceived value of a themed, transdisciplinary approach to service-learning. This study highlights promising practices for involving faculty in service-learning and, in keeping with an Appreciative Inquiry approach, depicts a view of faculty work at its best.

Linking Ethical Leadership and Employees’ In-Role Performance: Exploring the Mediating Roles of Psychological Capital and Follower-Leader Relational Capital

This study investigates the mediating impact of psychological capital and follower-leader relational capital on the relationship between ethical leadership and in-role performance through the lenses of social exchange theory, social information processing theory, and psychological resources theory. Analysis of data collected from a sample of 171 employees and 24 supervisors from Pakistan reveals that ethical leadership has a positive effect on followers’ in-role job performance, yet this effect is fully explained through the role of psychological capital and partially through follower-leader relational capital. Significant implications of these findings for further research and practice are discussed.

Using Network Analysis to Understand and Advance Falls Prevention Services and Programs

The purpose of this study was to understand referral linkages that exist among falls prevention agencies in a southern Ontario region using network analysis theory. This was a single case study which included fifteen individual interviews. The data was analyzed through the constant comparative approach. Ten themes emerged and are classified into internal and external factors. Themes associated with internal factors are: 1) health professionals initiating services; 2) communication strategies; 3) formal partnerships; 4) trust; 5) program awareness; and 6) referral policies. Themes associated with external factors are: 1) client characteristics; 2) primary and community care collaboration; 3) networking; and 4) funding. Recommendations to improve the referral pathway are: 1) electronic database; 2) electronic referral forms; 3) educating office staff; and 4) education days. This study outlined the benefit of using network analysis to understand referral pathways and the importance of implementing strategies that will improve falls prevention referral pathways.

A game-theoretic network formation model

We study the dynamics of a game-theoretic network formation model that yields large-scale small-world networks. So far, mostly stochastic frameworks have been utilized to explain the emergence of these networks. On the other hand, it is natural to seek for game-theoretic network formation models in which links are formed due to strategic behaviors of individuals, rather than based on probabilities. Inspired by Even-Dar and Kearns (2007), we consider a more realistic model in which the cost of establishing each link is dynamically determined during the course of the game. Moreover, players are allowed to put transfer payments on the formation of links. Also, they must pay a maintenance cost to sustain their direct links during the game. We show that there is a small diameter of at most 4 in the general set of equilibrium networks in our model. Unlike earlier model, not only the existence of equilibrium networks is guaranteed in our model, but also these networks coincide with the outcomes of pairwise Nash equilibrium in network formation. Furthermore, we provide a network formation simulation that generates small-world networks. We also analyze the impact of locating players in a hierarchical structure by constructing a strategic model, where a complete b-ary tree is the seed network.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Untangling the Organizational Ambiguities in Supply Chain Risk Recognition, Assessment, and Response: The Role of Network Embeddedness

In this thesis, I focus on supply chain risk related ambiguity, which represents the ambiguities firms exhibit in recognizing, assessing, and responding to supply chain disruptions. I, primarily, argue that ambiguities associated with recognizing and responding to supply chain risk are information gathering and processing problems. Guided by the theoretical perspective of bounded rationality, I propose a typology of supply chain risk related ambiguity with four distinct dimensions. I, also, argue that the major contributor to risk related ambiguity is often the environment, specifically the web of suppliers. Hence, I focus on the characteristics of these supplier networks to examine the sources of ambiguity. I define three distinct elements of network embeddedness – relational, structural, and positional embeddedness – and argue that the ambiguity faced by a firm in appropriately identifying the nature or impacts of major disruptions is a function of these network properties. Based on a survey of large North American manufacturing firms, I found that the extent of the relational ties a firm has and its position in the network are significantly related to supply chain risk related ambiguity. However, this study did not provide any significant support for the hypothesized relationship between structural embeddedness and ambiguity. My research contributes towards the study of supply chain disruptions by using the idea of bounded rationality to understand supply chain risk related ambiguity and by providing evidence that the structure of supply chain networks influences the organizational understanding of and responses to supply chain disruptions.

Understanding Network Governance: A Case Study Exploration of Active Canada 20/20

Consistent with the governance shift towards network forms of governance, a number of new social movements have formed in response to the declining levels of physical activity in the Western world. One such movement is Active Canada 20/20: A Physical Activity Strategy and Change Agenda for Canada. Network governance is employed as the theoretical framework for this case study exploration of Active Canada 20/20 and the political landscape surrounding its development and implementation. Semi-structured interviews were conducted in addition to document/policy analysis and direct observations. Analysis of the data resulted in three overarching themes – the defining characteristics of network governance, the political landscape, and intersectoral linkages – that interconnect multifariously based the nature of the Canadian federal government and its relationship with the voluntary sector for physical activity. Despite progress in driving Active Canada 20/20 forward, entrenched dynamics of power need to be navigated within the political landscape surrounding network governance.

Identification of Network-Based Risk Factors Associated with Gonorrhea

The evolving antimicrobial resistance coupled with a recent increase in incidence highlights the importance of reducing gonococcal transmission. Establishing novel risk factors associated with gonorrhea facilitates the development of appropriate prevention and disease control strategies. Sexual Network Analysis (NA), a novel research technique used to further understand sexually transmitted infections, was used to identify network-based risk factors in a defined region in Ontario, Canada experiencing an increase in the incidence of gonorrhea. Linear network structures were identified as important reservoirs of gonococcal transmission. Additionally, a significant association between a central network position and gonorrhea was observed. The central participants were more likely to be younger, report a greater number of risk factors, engage in anonymous sex, have multiple sex partners in the past six months and have sex with the same sex. The network-based risk factors identified through sexual NA, serving as a method of analyzing local surveillance data, support the development of strategies aimed at reducing gonococcal spread.

The Weekly Leader, Toronto, Ontario, June 16, 1866

The Weekly Leader, Toronto, Ontario, June 16, 1866.