Added Interest

Survey Activity Trap

In mid-2015 the AVMA distributed a survey.  It contained questions like, “How important is it for the veterinary profession to have a process for setting and applying educational standards to evaluate institutions granting veterinary degrees in the U.S.?”  The range of answer choices was: “Extremely important, Very important, Moderately important, Not very important, Not at all important.”

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AVMA Unable to Recognize Survey Methodology Fail

AVMA Economics Division head Michael Dicks and his team recently conducted a survey and concluded, "... the AVMA Report on Veterinary Employment published in March reported that weighted unemployment within the veterinary profession was 3.19% in 2014. To produce this number we obtained a sample of 1881 veterinarians. Since our membership consists of 72,174 veterinarians (excluding students) we are 95% confident in a .8% margin of error on both sides of the mean unemployment rate."

While we take issue with the unemployment number specifically, we take much greater issue with the failed methodology used to achieve the number, and the scientific failure it represents.  Particularly coming from an association that claims to value and promote science and the scientific method.

In an attempt to bring this to greater light, we wrote a Letter to the Editor of JAVMA.  Below is the subsequent exchange, as there was much go-round in an attempt to edit our claims and assertions.

Our side of the conversation is left-justfied and colored black.

The JAVMA side of the conversation has been right-justified and colored dark blue.

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2015 Veterinary Economics Career and Family Survey, pt2

Welcome to the second of a series of posts exploring the data from the 2015 Veterinary Economics Career and Family Survey.  We're gonna pick up where we left off in Part 1...



All that said and done, here’s the truly valuable part of this. Everything so far has been my interpretation.  I could have made mistakes.  Even if I didn’t, each person out there has their own set of priorities, their own questions, and their own way of looking at this data to answer the questions most relevant to them.

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