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Exploring Measurement Challenges in Diversity, Talent, and High-Tech Concepts

This study delves into the complexities of measuring talent, diversity, and high-tech concepts, questioning if the existing measures align with the actual constructs. It also examines cause-effect dynamics - does diversity drive talent or vice versa? We explore the importance of correct unit of analysis, statistical associations versus causal claims, and the impact of diversity on high-tech industries.

patrickcbrown
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Exploring Measurement Challenges in Diversity, Talent, and High-Tech Concepts

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  1. ISSUES Measurement issues: talent, diversity, coolness, high tech (do the measures fit the concepts?) Cause-effect issues (chicken+egg): does diversity lead to talent or talent (and education) to diversity? Cross-sectional patterns vs. longitudinal patterns (I.e., a “snapshot” of many places at one time vs. viewing a place across history and historical changes) Correct Unit of Analysis? (ecological fallacy?) Statistical associations (correlation) vs. causal claims.

  2. cause --> effect CONCEPTS DIVERSITY TALENT MEASURES Gay Index Percent BA/BS Degrees

  3. UNIT OF ANALYSIS

  4. Assumes cause-effect flows this way -->> dependent variable Intermediate variable

  5. Indirect effect -- mediated via talent Direct effect of diversity on high-tech

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