Industrial Psych Notes week of 4/4
Industrial Psych Notes week of 4/4 Psyc 3640
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This 4 page Class Notes was uploaded by Courtney Luber on Monday April 11, 2016. The Class Notes belongs to Psyc 3640 at Clemson University taught by Eric S McKibben in Fall 2016. Since its upload, it has received 20 views. For similar materials see Industrial Psychology in Psychlogy at Clemson University.
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Date Created: 04/11/16
4/04/2016 Chapter 6 cont’d Practical Issues in Staffing o Staffing Model Comprehensiveness Enough high quality information about candidates to predict likelihood of their success Compensatory Candidates can compensate for relative weakness in one attribute through strength in another one, providing both are required by job Combining Information o Clinical decision making Uses judgment to combine information & make decision about relative value of different candidates each person making decision uses own judgment can be almost impossible for humans to use a clinical decision making process when using a comprehensive approach o Statistical decision making Combines information according to a mathematical formula Regression equation Fewer errors in this approach o Hurdle system of combining scores Non-compensatory strategy: individual has no opportunity to compensate at later stage for low score in earlier stage Allows us to eliminate individuals easily i.e. if you don’t have at least 3 years of experience, you will be cut immediately Establishes series of cut scores o Hurdle System of Combining Scores Constructed from multiple hurdles so candidates who don’t exceed each of the minimum dimension scores are excluded from further consideration Often set up sequentially More expensive hurdles placed later Used to narrow a large applicant pool o Compensatory approach Multiple regression analysis Results in equation for combining test scores into a composite based on correlations of each test score with performance score Cross-validation Regression equation developed on first sample is tested on second sample to determine if it still fits well 4/06/2016 Score Banding o Individuals with similar test scores can be grouped together in a category or score band o Selection within band can be made based on other considerations o Score Banding is controversial o Score Banding uses the Standard error of measurement (SEM) for the test SEM provides a measure of the amount of error in a test score distribution Function of reliability of test & variability of test scores o Fixed band system Candidates in lower bands not considered until higher bands have been exhausted o Sliding band system Permits band to be moved down a score point when highest score in a band is exhausted Subgroup Norming o Develop separate lists for individuals in different demographic groups who are then ranked within their respective group o In general, subgroup norming is not allowed as a staffing strategy Selection vs. Placement o Sometimes, the challenge is to place an individual rather than simply select an individual o Placement Process of matching multiple applicants & multiple job openings Strategies Vocational guidance Pure selection Cut & fit Deselection o 2 typical situations Termination for cause Individual is fired for a particular reason Generally not unexpected Layoff Job loss due to employer downsizing or reductions in force Often occurs with little or no warning Large Staffing Projects o Concessions must be made: Labor intensive assessment procedures are often not feasible o Cost of testing can be quite expensive o Fairness is a critical issue o Standard, well-established, & feasible selection strategies are important Small Staffing Projects o Luxury of using wider range of assessment tools o Adverse impact is less of an issue o Fairness is still a key issue o Rational, job-related, & feasible selection strategies are important Legal Issues in Staffing Decisions o Charges of employment discrimination Involve violations of Title VII of 1964 CRA, ADA, or ADEA I-O psychologists often serve as expert witnesses in these lawsuits Consequences can be substantial Most often brought by individual claiming unfair termination Intentional Discrimination or Adverse Treatment o Plaintiff attempts to show that employer treated plaintiff differently than majority applicants or employees Unintentional Discrimination or Adverse Impact (AI) o Acknowledges employer may not have intended to discriminate against plaintiff but employer practice had AI on group to which plaintiff belongs Determination of Adverse Impact o Burden of proof on plaintiff to show: a) he/she belongs to a protected group, & b) members of protected group were statistically disadvantaged compared to majority employees “80%” or “4/5ths” rule o Guideline for assessing whether there is evidence of Adverse Impact (AI) o Plaintiffs must show that protected group received only 80% of desirable outcomes received by majority group in order to meet burden of demonstrating AI o Results in AI ratio o Can be substantially affected by sample sizes o Burden of proof shifts to employer once AI is demonstrated Social Networking Sites and the Workplace o Employees (or applicants) posting information on a social networking site (e.g., Facebook, Twitter) that is accessed by an employer have been increasingly getting in trouble. o Job candidates who have been found to post on SNS that they like to “shoot people” or “blow things up” have been removed from hiring consideration. o Employment lawyers are still debating the legality of employment decisions based on information on social networking sites.
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