Group Consensus Support Helping Clarify Group Opinion by Visualizing the Matrix of Judges, Projects, and Scores David I. Feinstein, Ph.D. www.AnalyticAnimations.com dif@alumni.caltech.edu Group consensus with partial information has even merited the attention of evolution! Honey bees, biologists recently figured out, prefer quorums. In late spring, colonies divide, with the queen and half the workers leaving the old hive. The swarm forms a cluster outside its old home and goes about finding new digs. But the queen doesn't choose. Instead, the bees engage in what biologist Thomas Seeley of Cornell University calls "a plebiscite, where once you have a quorum in favor of one site it wins.“ . . . "The beauty of this process is that quorum sensing results in selection of a great site even though no one scout knows all the alternatives out there“ When 10,000 honeybees fly the coop to hunt for a new home, they have a unique method of deciding which site is right: With great efficiency they narrow down the options and minimize bad decisions. Their technique, includes coalition building until a quorum develops. © 2009 David I. Feinstein From the Database of Scores to a Graphic Display of Scores & Quartiles • top quartile ° second quartile ° third quartile 94 93 90 90 ET007 ET042 ET014 ET003 ET055 ET005 ET053 ET051 96 91 82 78 75 67 61 47 ET028 ET042 ET036 ET020 ET014 ET045 92 77 76 76 72 69 68 62 ET020 ET042 ET056 ET016 ET034 ET024 ET032 ET057 93 92 87 78 78 75 72 71 ET037 ET042 ET045 ET005 ET052 ET007 ET053 ET024 ET042 ET057 ET003 ET005 ET016 99 99 98 ET042 ET034 ET055 ET003 ET014 ET053 ET051 ET007 93 90 89 88 85 48 85 82 75 73 48 • bottom ET042quartile J55896 J55077 ET020 88 J56064 ET005 78 J55459 ET003 70 J56182 ET014 65 J56106 ET042 57 J56169 ET057 57 J55685 ET051 ET032 48 40 ET055 ET014 ET042 ET053 ET057 ET003 ET032 ET051 93 91 82 82 72 69 61 51 95 92 92 91 90 82 82 57 Score Display with Quartile Rankings • top quartile ° second quartile ° third quartile • bottom quartile ISEF 2007 category ET sorted by average score Discrepant quartiles are important! these mark judges with something to say © 2009 David I. Feinstein Beyond Average Scores: Comparing All Scores of a Project Pair second project How often does a score from the first project beat a score from the second project? first project 36.7% 100 96 93 91 81 72 62 86.0 92 0 0 0 0 1 1 1 1 91 0 0 0 0 0.5 1 1 1 90 0 0 0 0 0 1 1 1 89 0 0 0 0 0 1 1 1 88 0 0 0 0 0 1 1 1 84 0 0 0 0 0 1 1 1 79 0 0 0 0 0 0 1 1 78 0 0 0 0 0 0 1 1 86.4 © 2009 David I. Feinstein 93 How much would the “all scores” comparison change if we reran the science fair with a new assignment of judges to projects? Simulate these new assignments by resampling the projects’ scores: 92 0 0 92 0 0 91 0 0 42.2% 96 91 93 92 0 91 0 89 91 0 88 0 0 0 88 88 0 91 91 81 72 62 85.1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0.5 91 0.572 1 621 0.5 0.5 0.5 0.5 930 91 0 0 0 91 0 0.5 0.5 0.5 1 0 0 1 0 1 0 0 0 0 0.5 0.5 0 0 0 1 0 00 0 1 1 1 62 82.5 1 1 1 1 1 1 11 1 1 1 11 11 1 1 00 00 0 96 0 910 81 0 81 1 172 162 92 84 0 0 0 0 0 0 10 10 1 1 11 11 92 79 0 0 0 0 0 0 10 10 1 1 1 1 0 1 1 1 0 1 1 1 45.3%84100 0 92 79 0 78 90 0 90.3 96 0 0 0 0 0 0 1 0 0 0 1 1 1 1 1 1 0 0 0 0 1 1 1 1 90 0 0 0 0 1 1 1 1 79 0 0 0 0 0 0 1 1 78 0 0 0 0 0 0 1 1 78 0 0 0 0 0 0 1 1 86.4 84.4 84.9 39.1 a b c a a b 1 19.5 25.0 46.1 70.3 21.9 a c c a b c b b b the first project beats the second in 2000 of 10,000 rerun science fairs 48.4 “All Scores” comparison 53.9% 100 93 list of resampled comparisons Significance of “All Scores” Comparison 0.8 0.6 0.4 0.2 53.9 0 42.2 45.3 0 3 210 3 410 3 610 3 810 4 110 position in sorted list of resampled comparisons © 2009 David I. Feinstein 2nd Display: Project Comparison Matrix project 007 95 93 100 97 96 95 93 98 96 96 94 90 90 100 96 96 95 95 93 0.5 1 1 1 1 1 0 0.5 0.5 1 1 1 0 0.5 0.5 1 1 1 0 0 0 0.5 0.5 1 0 0 0 0.5 0.5 1 0 0 0 0 0 0.5 0.5 0 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0.5 0.5 0 0.5 0.5 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 100 97 96 95 93 87 0.5 1 1 1 1 1 0 1 1 1 1 1 0 0.5 0.5 1 1 1 0 0 0 0.5 0.5 1 0 0 0 0 0 0.5 0 0 0 0 0 0 0.5 1 1 1 1 1 0 0.5 1 1 1 1 0 0 0.5 1 1 1 0 0 0 0.5 1 1 0 0 0 0 0.5 1 0 0 0 0 0 0.5 1 1 1 0 1 1 0 0.5 0.5 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 1 1 1 1 1 0 1 1 1 1 1 0 98 96 96 94 90 90 0 1 1 0 0.5 0.5 0 0.5 0.5 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 1 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1 1 0 0.5 1 1 0 0.5 1 1 0 0 0.5 1 0 0 0.5 1 0 0 0 0.5 87 project 007 95 project 004 96 project 060 project 060 100 96 project 004 1 1 0 0.5 0 0.5 0 0 0 0 0 0 1 1 1 0 0 0 1 1 1 1 0 0 1 1 1 1 1 1 0.5 1 1 1 1 1 0 0.5 0.5 1 1 1 0 0.5 0.5 1 1 1 0 0 0 0.5 1 1 0 0 0 0 0.5 0.5 0 0 0 0 0.5 0.5 Ordering by average score occasionally yields a consistent comparison matrix Numbers indicate the percentage of rerun science fairs in which the project owning the row beats the project owning the column by the all–scores comparison measure. © 2009 David I. Feinstein Comparison matrix anticipates ISEF 2007 MI category award assignments start: projects ordered by average rank © 2009 David I. Feinstein end: projects ordered by award level ISEF 2007 ET: comparison matrix spots 007! © 2009 David I. Feinstein Group Consensus Support Project Score Display quartile markers show scores & gauge their significance Project Comparison Matrix binary comparison outcomes of all pairs of projects departures from triangular structure highlight projects meriting judges’ attention discrepant quartiles mark judges with something to say © 2009 David I. Feinstein