Meritocracy Voting: Measuring the Unmeasurable
Learned societies commonly carry out selection processes to add new fellows to an existing fellowship. Criteria vary across societies but are typically based on subjective judgments concerning the merit of individuals who are nominated for fellowships. These subjective assessments may be made by existing fellows as they vote in elections to determine the new fellows or they may be decided by a selection committee of fellows and officers of the society who determine merit after reviewing nominations and written assessments. Human judgment inevitably plays a central role in these determinations and, notwithstanding its limitations, is usually regarded as being a necessary ingredient in making an overall assessment of qualifications for fellowship. The present paper suggests a mechanism by which these merit assessments may be complemented with a quantitative rule that incorporates both subjective and objective elements. The goal of 'measuring merit' may be elusive but quantitative assessment rules can help to widen the effective electorate (for instance, by including the decisions of editors, the judgments of independent referees, and received opinion about research) and mitigate distortions that can arise from cluster effects, invisible college coalition voting and inner sanctum bias. The rule considered here is designed to assist the selection process by explicitly taking into account subjective assessments of individual candidates for election as well as direct quantitative measures of quality obtained from bibliometric data. The methodology has application to a wide arena of quality assessment and professional ranking exercises.
|Date of creation:||Oct 2011|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.yale.edu/
More information through EDIRC
|Order Information:|| Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA|
When requesting a correction, please mention this item's handle: RePEc:cwl:cwldpp:1833. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Glena Ames)
If references are entirely missing, you can add them using this form.