Collective Negotiation for Public and Professional Employees: Text and Readings.

Companies always seek ways to make their professional employees stay with them to reduce extra recruiting and training costs. Predicting whether a particular employee may leave or not will help the company to make preventive decisions. Unlike physical systems, human resource problems cannot be described by a scientific-analytical formula. Therefore, machine learning approaches are the best tools for this aim. This paper presents a three-stage (pre-processing, processing, post-processing) framework for attrition prediction. An IBM HR dataset is chosen as the case study. Since there are several features in the dataset, the “max-out” feature selection method is proposed for dimension reduction in the pre-processing stage. This method is implemented for the IBM HR dataset. The coefficient of each feature in the logistic regression model shows the importance of the feature in attrition prediction. The results show improvement in the F1-score performance measure due to the “max-out” feature selection method. Finally, the validity of parameters is checked by training the model for multiple bootstrap datasets. Then, the average and standard deviation of parameters are analyzed to check the confidence value of the model’s parameters and their stability. The small standard deviation of parameters indicates that the model is stable and is more likely to generalize well.

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Current Hiring Practices of Campus Recreation Directors of NIRSA Institutions

Recreational Sports Journal ◽

10.1123/rsj.30.2.100 ◽

2006 ◽

Vol 30 (2) ◽

pp. 100-115 ◽

Cited By ~ 2

Author(s):

William F. Stier ◽

Robert C. Schneider ◽

Stephen Kampf ◽

Gregory Wilding ◽

Scott Haines

Keyword(s):

Hiring Practices ◽

Professional Organizations ◽

Campus Recreation ◽

Job Descriptions ◽

Public And Private ◽

Graduate Assistants ◽

Entry Level ◽

Policies And Procedures ◽

Recreation Directors ◽

Professional Employees

A survey of all National Intramural-Recreational Sports Association (NIRSA) campus recreation directors was conducted to determine the hiring practices, policies, and procedures relating to professional employees, graduate assistants, and student employees in campus recreation programs throughout North America. The survey instrument, in its final form, addressed hiring practices, policies, and procedures of campus recreation directors through 28 questions relating to the following areas: (a) search and screen committees, (b) job descriptions, (c) advertisement and announcement of vacancies, (d) applications, (e) references, (f) interviews, and (g) impact/involvement of national professional organizations in the hiring process. Selected data is presented in terms of (a) entry level position (coordinator) or for mid-level positions, (b) size of institutions (small, medium, and large), (c) rural, urban, and suburban locations, and (d) public and private institutions.

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