Come out swinging Trimbur, Lucia
2013., 20130825, 2013, 2013-08-25
eBook
Gleason's Gym is the last remaining institution of New York's Golden Age of boxing. Jake LaMotta, Muhammad Ali, Hector Camacho, Mike Tyson--the alumni of Gleason's are a roster of boxing greats. ...Founded in the Bronx in 1937, Gleason's moved in the mid-1980s to what has since become one of New York's wealthiest residential areas--Brooklyn's DUMBO. Gleason's has also transformed, opening its doors to new members, particularly women and white-collar men.Come Out Swingingis Lucia Trimbur's nuanced insider's account of a place that was once the domain of poor and working-class men of color but is now shared by rich and poor, male and female, black and white, and young and old.
Come Out Swingingchronicles the everyday world of the gym. Its diverse members train, fight, talk, and socialize together. We meet amateurs for whom boxing is a full-time, unpaid job. We get to know the trainers who act as their father figures and mentors. We are introduced to women who empower themselves physically and mentally. And we encounter the male urban professionals who pay handsomely to learn to box, and to access a form of masculinity missing from their office-bound lives. Ultimately,Come Out Swingingreveals how Gleason's meets the needs of a variety of people who, despite their differences, are connected through discipline and sport.
•SL, DL and DRL models were constructed for multi performance prediction of gymnasiums under different weather conditions.•Accuracy, time, interpretability, ease-of-use, hyperparameters, and ...robustness of the metamodels have been investigated.•Energy consumption, temperature and CO2 time series vectors prediction were modeling with nine training sets.•Methodology for hyperparameters comparison using exhaustive grid search and sensitivity analysis.•RDPG is most accurate but time-consuming. LSTM is more efficient and also has relatively excellent accuracy.
Building performance simulation (BPS) is essential for testing energy demand and indoor environment quality of different building designs. However, software for BPS is computationally intensive and impractical to run thousands even millions of simulations for performance analysis and optimization. Especially for the large space buildings, which usually have complex forms and high energy consumption. The computational problem could be overcome by the adoption of metamodels. Most correlational research focuses on single performance prediction of a particular building, which makes the model less robust when applied to multi vectors prediction for different buildings under multiple weather conditions. This paper leveraged six metamodels, which include recurrent deterministic policy gradient (RDPG), asynchronous advantage actor-critic (A3C), long short-term memory (LSTM), convolution neural network (CNN), artificial neural network (ANN) and support vector regression (SVR), to predict hourly-based multi performance vectors of gymnasiums under various design parameters and multiple weather conditions. Six metamodels are trained and tested on a large scale of datasets simulated by EnergyPlus over four gymnasium cases in different cities of China. The accuracy, efficiency, ease-of-use, robustness and interpretability of the models are investigated. To conduct a fair and detailed comparison, a methodological approach using grid searches for model settings selection assisted by sensitivity analysis is pursued. Principal component analysis (PCA) is also adopted to interpret the work process of the metamodels. The comparison showed that the RDPG model provides the most accurate prediction results with R2 converges at 0.993, 0.982 and 0.941 for energy, temperature and CO2, respectively. LSTM model is more efficient than RDPG, and suitable for users who need emphasis on both time and accuracy. ANN is suitable for users with limited time and require models of ease-of-use and robustness. SVR and ANN could be used for the automatically co-simulation with BPS software. In future research, the influence of occupant behavior also should be investigated.
Evacuation in university gymnasiums is a critical issue for campus safety. Human factors play an important role in the evacuation process. In order to explore the human factors that influence ...evacuation performance in university gymnasiums, this study conducted a questionnaire survey to 1287 participants. The data from the questionnaire survey were analysed by factor analysis, multiple linear regression analysis and T-test. The results showed that there were four human factors that affected evacuation performance in university gymnasiums: crowdedness, familiarity, attention and subjective physical condition. Among which familiarity and subjective physical condition had positive effects, while crowdedness and attention had negative impacts. Gender differences in participants’ evacuation performance were observed as well. The findings will help researchers to understand the evacuation in university gymnasiums comprehensively, and provide instructions for the prevention of evacuation accidents.
•A questionnaire survey is conducted to study human factors in university gymnasium evacuation.•Crowdedness, familiarity, attention and subjective physical condition have major impacts on evacuation performance.•Familiarity and subjective physical condition have positive effects, while crowdedness and attention have negative effects.•Gender differences also play a role in participants’ evacuation performance.
We implement a gym-attendance incentive intervention and elicit subjects' predictions of their postintervention attendance. We find that subjects greatly overpredict future attendance, which we ...interpret as evidence of partial naiveté with respect to present bias. We find a significant postintervention attendance increase, which we interpret as habit formation, and which subjects appear not to predict ex ante. These results are consistent with a model of projection bias with respect to habit formation. Neither the intervention incentives, nor the small posttreatment incentives involved in our elicitation mechanism, appear to crowd out existing intrinsic motivation. The combination of naiveté and projection bias in gym attendance can help to explain limited take-up of commitment devices by dynamically inconsistent agents, and points to new forms of contracts. Alternative explanations of our results are discussed.
Data, as supplemental material, are available at
http://dx.doi.org/10.1287/mnsc.2014.2091
.
This paper was accepted by Uri Gneezy, behavioral economics.
The article deals with the issue of teaching the Law of God in gymnasiums and other secondary educational institutions of the Russian Empire during the 19th — early 20th century and attempts to ...regulate it on the part of the state and church authorities. During this period, the subject was introduced as mandatory, but the results of its teaching constantly caused complaints from both students and teachers. For a century there was a search for the most favourable forms and methods of teaching the Law of God. The Catechism of Metropolitan Philaret (Drozdov), created at this time, was met with criticism and was edited several times by the author, and each revision solved some problems, but at the same time posed new ones. In this regard, numerous attempts were attested to create various kinds of manuals based on Metropolitan Philaret’s Catechism which was approved by the programme. However, until the Bolshevik seizure of power, when the teaching of the Law of God was cancelled, its critics argued that the study of this subject never achieved its main goal of training people who would be religiously educated, moral and faithful servants of the Church and Fatherland. The discussion was interrupted by the Bolsheviks’ abolition of the very subject of the Law of God in educational institutions, and therefore left open the question of how the course could achieve its goal.
The purpose of the article is to review some aspects of pedagogical education establishment in Russia in the first half of the 19th century. The author outlines that the period of the reign of ...Emperor Alexander I was characterized by a large-scale educational reform, the purpose of which was to create a single multi-level education system. Its implementation required a large number of teachers. It is emphasized that the solution of the problem of training teachers for gymnasiums was entrusted to the universities. Gymnasium, in turn, had to prepare teachers for primary schools.
During the study the following methods and materials were used: analysis of documentary sources, assessments on the development of Russian education, published in the second half of the 19th – early 20th centuries.
It is concluded that state structures attached great importance to the system of pedagogical education. Measures on training teachers for secondary and primary schools were taken. It is pointed out that the most important place has begun to be occupied by activities related to the training of teachers for the primary public education system. The existing system of pedagogical education was developed during the reign of Nicholas I. Its most important component was the Main Pedagogical Institute established in Saint Petersburg.
Hypothetical purchase tasks are a widely used tool to determine the reinforcing value of commodities, especially commodities which are difficult to deliver experimentally. Amazon Mechanical Turk ...users (
N
= 375) completed two novel hypothetical purchase tasks (quantity of purchase and probability of purchase) and other measures to estimate how much an individual values the opportunity to exercise in a gym. We examined correlations between demand indices generated by each task and measures related to physical activity. In addition, we compared rates of systematic and nonsystematic responding between the two tasks. Exploratory analyses of demand indices and measures of physical activity suggest initial evidence of construct validity for each task. When accounting for an order effect, the probability of purchase task generated significantly lower rates of nonsystematic responding compared to the quantity of purchase task (2.87% vs. 14.6%, respectively). We discuss how these results may inform improved construction of future hypothetical purchase tasks and implications for using likelihood and quantity purchase tasks.
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