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Selection 2

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Texas Accents Y'all ... Texas hiring managers look favorably on applicants with pronounced Texas accents. ... whose regional accents are less distinguishable, ... – PowerPoint PPT presentation

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Title: Selection 2


1
Selection 2
  • MANA 4328
  • Dr. George Benson
  • benson_at_uta.edu

2
Selection Bias
  • White Sounding Names
  • The professors at U. of Chicago and MIT sent
    about 5,000 resumes in response to want ads in
    The Boston Globe and Chicago Tribune.
  • White" names received 1 response for every 10
    resumes mailed, while "black" applicants with
    equal credentials received 1 response for every
    15.
  • Texas Accents Yall
  • Study by U. of North Texas researchers has found
    that Texas hiring managers look favorably on
    applicants with pronounced Texas accents.
  • Speakers from California and Minnesota, whose
    regional accents are less distinguishable,
    generally do better with managers all across the
    country.

3
Selection Tests and Litigation
  • Unstructured interviews
  • Cognitive ability tests
  • Physical ability tests
  • Structured interviews
  • Work sample tests
  • Assessment Centers

More likely to be challenged in court.
4
Substantive Methods
  • Training and Experience Checklists
  • Weighted Application Blanks (WABs)
  • Biodata
  • Interviews
  • Ability Tests
  • Proficiency Tests
  • Assessment Centers
  • Personality Tests
  • Integrity Tests

5
Methods to Improve Initial Selection
  • How can organizations encourage honesty in
    applications and resumes?
  • Training and Experience Evaluations (Checklists)
  • Holistic Judgment
  • Point Method
  • Task-based and KSA-based
  • Weighted Applications

Validity
6
Weighted Application Blanks
7
Developing WABs
  • Choose criterion
  • Performance characteristics of the job
  • Identify groups
  • Typically high performers and low performers
  • Select application items and response categories
  • Things that are likely relevant to performance
  • Determine weights based on group differences
  • Validate weights using a holdout sample
  • Set cutoff scores based on validation results

8
Biodata Inventories
  • Reliable Valid (r .32 to .37)
  • Series of questions on a wide variety of subjects
  • Background (e.g. hobbies, jobs, and education)
  • Situational questions
  • Personality and Values
  • Compared to a profile generated from successful
    employees or database for occupations.

9
Examples of Biographical Questions
  • How many jobs have you held in the last five
    years?
  • Were you ever class president?
  • Have you ever repaired a broken radio so that it
    later worked?
  • While growing up, did you collect coins?
  • When you were a teenager, how often did your
    father help you with schoolwork?
  • About how many fiction books have you read in the
    past year?
  • How many hours a week do you spend studying?
  • By the time you were 18 had you traveled at least
    500 miles from home by yourself?

10
Profile Matching
  • D2 S (P(ideal) P(applicant))2
  • Develop a set of target or ideal scores by
    sampling high performers.
  • For each item subtract the applicants scores
    from the ideal score and square the result.
  • Sum the squares of the difference scores.
  • Smaller D scores more closely resemble the
    ideal candidate.

11
  • Why use Biodata?
  • Why not use Biodata?
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