How are the correlations calculated?
Linear (Pearson) correlations were computed by assigning numeric values to variables as follows.
||For each possible answer A to a given question Q, we assign the variable 'Q:A' either an undefined value or a defined a value between -2 and 2 as follows:
Note that some answers have been combined in order to diminish the dimensionality of the data:
- 2 for 'Accept: A'
- 1 for 'Lean towards: A'
- undefined if skipped question or answered 'insufficiently familiar with the issue'
- 0 for any other answer but a 'Lean towards: X' or 'Accept: X' answer
- -1 for 'Lean towards: X', where X is one of the alternatives to A for question Q
- -2 for 'Accept: X', where X is one of the alternatives to A for question Q
- Relativism and contextualism about knowledge claims have been combined under the heading of variantism
- Qualia theory and sense-datum theory have been conflated under the heading of qualia-or-sense-data.
- Skepticism and idealism have been conflated under the heading of skepticism-or-idealism
||The variable 'metasurvey:accuracy' encodes the negation of respondents' normalized average error (?).
||Values are left unchanged.
||'gender:female' = 2 if the respondent specified 'female' as gender, -2 if the respondent specified 'male' as gender, and undefined otherwise.
||For the purposes of calculating linear correlations, we have considered only the analytic-continental dimension. The variable 'tradition:analytic' = 2 when the respondent specified 'analytic' as tradition, -2 when the respondent specified 'continental' as tradition, and 0 otherwise.
|All other answers
||All other answers were treated as categorical variables. For example, an individual has 2 for 'AOS::Metaphysics' if he or she has specified Metaphysics as AOS, and -2 otherwise.
Often, positively (or negatively) correlated variable pairs have corresponding negatively (or positively) correlated variable pairs. We have sought to display only the most natural correlation (usually the positive correlation).
Significance of correlations
We have not included significance measures, partly because these are problematic when so many correlations are being calculated. But to give a rough idea, a one-off correlation coefficient of 0.1 (our cutoff for inclusion on the "most correlated answers" list) over a population of 931 subjects (the number of target faculty respondents, whose answers are used here) yields a p-value of 0.002.
Of course given that there are 5,675 pairs of answers to correlate, one would then expect that even in the absence of genuine correlations, there would be around 11 correlation coefficients that are over this cutoff by chance alone.