Detector-dog organizations continually work to improve their effectiveness. Detector dogs commonly work in partnership with human handlers. Organizations spend considerable amounts of resources selecting both dogs and humans suited for the required duties. This thesis describes two studies. In the first study, we developed and evaluated a subjective dog trait-rating survey to obtain ratings of dogs by the people raising them. In the second study, we examine how human characteristics relate to job performance for professional detector-dog handlers. In working-dog breeding programs, candidate puppies are often placed with volunteer families (puppy raisers) who care for and raise the puppies. These families have extensive opportunities to observe a puppy’s behavior across time so they may be able to make accurate trait evaluations, which could predict subsequent performance. In Study 1, we develop, implement, and evaluate the Puppy Raiser Subjective Survey (PRS Survey) on a population of puppy raisers from a large detector-dog organization (Australian Customs & Border Protection Service; AC&BPS). Analyses identified seven dimensions of personality but a model including these variables was not able to significantly predict working performance. Selecting people who are suited to work as dog handlers is likely to be important to the success of working-dog programs. Detector-dog programs often undergo a resource intensive process to select the best humans for the job. However, there has been scarce research on the types of traits that make one handler more effective than another. In Study 2, we develop, implement, and evaluate an instrument used to identify human characteristics that predict success as AC&BPS detector-dog handlers. We show that job seniority was the strongest predictor of detector-dog handler job performance. We also show intriguing possibilities that participation in a greater number of sports, particularly at competition levels, may correlate with better job performance. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/26527 |
| Date | 14 October 2014 |
| Creators | Debono, Stephen Nicholas |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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