The Judgment of Paris According to Borda

Hulkower, Neal D.

doi:10.1080/09571260903451029

Cited by 18 publications

(22 citation statements)

References 8 publications

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“…Eleven experts (nine of them French) tasted ten reds (six California and four French) and ten whites (again, six California and four French). Although much has been written about who “won” the tasting (e.g., Ashenfelter and Quandt, 1999; Cicchetti, 2004a; Hulkower, 2009; Lindley, 2006; Quandt, 2006, 2007), my concern here is the extent to which the 11 judges agreed in their judgments of the wines. Cicchetti (2004a, 2006b), using the intraclass correlation coefficient as the measure of judge consensus, finds an overall consensus level of .22 for the reds and .36 for the whites.…”

Section: Resultsmentioning

confidence: 99%

Reliability and Consensus of Experienced Wine Judges: Expertise Within and Between?

Ashton

2012

J Wine Econ

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This paper considers the levels of reliability and consensus of wine quality judgments found in studies of experienced wine judges. Both reliability, which concerns the similarity of repeat judgments of a particular wine by the same judge, and consensus, which concerns the similarity of judgments of a particular wine across judges, are necessary requirements for expertise in wine judging. Reliability and consensus levels found in wine judging are compared to those documented by a large body of research in six other fields: medicine, clinical psychology, business, auditing, personnel management, and meteorology. In all fields, including wine judging, reliability is greater than consensus. Both reliability and consensus are, on average, substantially lower in wine judging than in other fields, although tremendous variability exists across judges in every field. Overall, little support is found for the idea that experienced wine judges should be regarded as experts. (JEL Classification: C91)

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Section: Resultsmentioning

confidence: 99%

Reliability and Consensus of Experienced Wine Judges: Expertise Within and Between?

Ashton

2012

J Wine Econ

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“…Scores assigned by individual tasters in Paris are from Hulkower (2009, Tables 3 and 8), in Princeton from Ashenfelter and Storchmann (2012, Tables 3 and 4), for Affairs from its website affairsofthevine.com, 1 for Lisbon from Professor Manuel Malfeito Ferreira of Instituto Superior de Agronomia, Universidade de Lisboa, 2 and for FOG from the author. Scores between 0 and 20, ties allowed, were assigned in Paris and Princeton 3 .…”

Section: Scores For Women and Men In Twenty-three Tastingsmentioning

confidence: 99%

Wine, Women, Men, and Type II Error

Bodington¹

2017

J Wine Econ

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More than forty published works show that women and men differ in their taste preferences for sweet, salt, sour, bitter, fruit, and other flavors. Despite those differences, dozens of state fair and other wine competitions determine winners' ribbons, medals, scores, and ranks by pooling the opinions of female and male judges. This article examines twenty-three blind wine tastings during which female and male judges scored more than nine hundred wines. Two-sample t-test results show that the gender-specific distributions of scores do have similar means and standard deviations. Exact p-values for two-sample chi-square tests show that the distributions of men's and women's scores are not significantly different, and exact p-values for likelihood ratio tests of Plackett-Luce model results show that the genders' preference orders are not significantly different. The correlation coefficient between women's and men's scores is weakly positive in 90 percent of the tastings. On that evidence, indications that the genders prefer different wines are difficult to detect. If such differences do exist, as the nonwine literature implies, the results of this analysis show that those differences are small compared to non-gender-related idiosyncratic differences between individuals and random expressions of preference. The potential for accept-a-false-null-hypothesis Type II error when pooling female and male judges' wine-related opinions appears to be small. (JEL Classifications: A10, C10, C00, C12, D12)

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“…Borges, et al (2012) dismiss the aggregation method used by Quandt (2006) because it “does not respect the Condorcet property.” Quandt's method, which he calls “votes against,” is in fact equivalent to the Borda Count (Hulkower, 2009). A key attribute of the Borda Count is that it uses all of the information provided by each voter whereas the Condorcet property ignores critical information, specifically the intensity of preference.…”

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confidence: 99%