Law

An ever-growing chorus of academicians report that with the expanding number of academic journals there is a concomitant increase in the number of articles based on questionable methodology.  Many published studies contain improper statistical conclusions, flawed methodology, and results that cannot be replicated.  The recent controversy concerning the failure of parents to vaccinate their children because of the recommendations of flawed research exemplifies this crisis. This epidemic of faulty research has been exacerbated recently by the spread of low-quality academic journals and “pay-to-publish” journals, which will publish virtually anything for a fee.  This Article provides an analysis of a growing crisis of reliability in scientific research and how the so-called “researchers’ privilege” allows faulty research to go undetected.  This Article delineates the reasons why it is difficult, if not impossible, to evaluate published research findings without access to the underlying information that researchers have in their possession.  The Article then analyzes the state of the law regarding the ability of researchers to withhold records and data based on the so-called “researchers’ privilege.”  Finally, the Article explains why courts should favor the disclosure of research data and that confidentiality concerns should be addressed by a confidentiality order.

[S\ome statistical errors in research publications transcend mere misunderstanding and instead show that researchers manipulate statistical methods to obtain the desired results.  Psychologist Uri Simonsohn calls this phenomena “P-hacking,” and others refer to it as “data-dredging, snooping, fishing, significance-chasing and double-dipping.”  Statistics defines the P-value as “the probability that an observed positive association could result from random error even if no association were in fact present.”  For example, suppose that in an epidemiology study investigating the potential association between the administration of vaccines and the development of side effects, the P-value is 0.05. This P-value indicates that even if the vaccine had no effect, a positive association could be obtained in 5% of the studies due to random-sampling error.  Unfortunately, researchers can manipulate this relatively straightforward statistic.