The Data, or Information Quality Act, officially known as Section 515 of the United States Treasury and General Government Appropriations Act for Fiscal Year 2001, is a watershed of sorts for anti-regulatory interests.  The legislation, which was enacted without any public debate or hearings, was quietly "attached as an appropriations rider" to a voluminous spending bill (Wagner, 2004, p. 64).

The Data Quality Act (DQA), as written, is a relatively brief and indistinct document, and as expressed by Sydney Shapiro (2004), the simplest method of describing the document is reprinting it in its entirety:

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Section 515 - Data Quality Act

A.    In General -- The Director of the Office of Management and Budget shall, by not later than September 30, 2001, and with public and Federal agency involvement, issue guidelines under sections 3504(d)(1) and 3516 of title 44, United States Code, that provide policy and procedural guidance to Federal agencies for ensuring and maximizing the quality, objectivity, utility, and integrity of information (including statistical information) disseminated by Federal agencies in fulfillment of the purposes and provisions of chapter 35 of title 44, United States Code, commonly referred to as the Paperwork Reduction Act.
     B.  Content of Guidelines. - The guidelines under subsection (A) shall-
          1.  apply to the sharing by Federal agencies of, and access to, information disseminated by Federal agencies; and
          2.  require that each Federal agency to which the guidelines apply-
               a.  issue guidelines ensuring and maximizing the quality, objectivity, utility and integrity of information (including statistical information) disseminated by the agency, by not later than 1 year after the date of issuance of the guidelines under subsection (A);
               b.  establish administrative mechanisms allowing affected persons to seek and obtain correction of information maintained and disseminated by the agency that does not comply with the guidelines issued under subsection (A); and
               c.  report periodically to the Director-
                    i.  the number and nature of complaints received by the agency regarding the accuracy of information disseminated by the agency; and
                    ii.  how such complaints were handled by the agency.
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While the document itself does not, at first glance, suggest substantial repercussions, the legal interpretation of the rider is where the debate begins and implications of its use become unclear.  

"Sound Science" and Daubert

At the forefront of this assault of regulation is the emergence of the "sound science" debate.  Sound science, proponents claim, is a necessary basis for improved regulation.  The core philosophy of this movement is to engage in more peer review in the research process.  While science generally encourages diversity of participation in experiments, no specific research points to improved accuracy with peer review.  In fact, Lacko (2004) states that a significant "problems [exist with peer review] including the connection between a researcher's funding and that researcher's scientific findings" (p. 321).  Lacko stresses that "corporate dominance affects what is to be researched, what is to be published, and thus, what is to be suppressed" (p. 322).  Indeed, sponsors often retain control over the publication of study results.

Hornstein (2004) similarly argues that the most dangerous trend affecting the regulatory process is the influence of corporate sponsors on university-based research.  Long held as the most reliable source of subjective data, university researchers are under pressure from many of the private enterprises that fund their research.  There is a concern that "corporate sponsorship influences the mindset of university researchers, who edit themselves lest they jeopardize their sponsors" (p. 242).

Hornstein (2004) further criticizes the sound science movement by pointing out that in many cases, such as the "EPA's ozone and particulate matter revisions, when `good science' is held up to the mirror, many of its proponents only want to see one thing - `their science'" (p. 237).

Interestingly, Burke (2004) observes that "the use of sound science implies that one of the major problems with [regulation] is a preponderance of `bad science'" (p. 501).  Indeed, the implication has been made, and has found legal support in a landmark Supreme Court case referred to as Daubert.  In this case the Supreme Court ruled particular evidence to be inadmissible due to the unreliability of the scientific methodology used in its acquisition.  Proponents claim that "'regulatory Daubert' encourages reviewing judges to be less deferential, and thus more probing, of agency science and related administrative justifications for regulatory action" (Raul & Dwyer, 2004, p.7).

Daubert "empowered federal judges to reject irrelevant or unreliable scientific evidence [and has] given the judiciary a mandate to foster `good science' in the courtroom and reject expert testimony not grounded in scientific methods and procedures" (Raul & Dwyer, 2004, p. 7).  Unfortunately, it is unclear whether judicial review can be useful; after all, what makes a judge a good evaluator of scientific method or validity.  At best, they can attempt to ensure scientific method, but not guarantee accuracy.  To this end, Daubert is rarely effectively invoked.

Genesis of the Data Quality Act

To gauge the probable intent of the DQA, it is necessary to establish the probable intent of the architects of the legislation.  The Data Quality Act was authored by Jim Tozzi, "head of the corporate-sponsored Center for Regulatory Effectiveness" (Lacko, 2004, p. 307).

"Tozzi earned a degree in economics and rose to OMB deputy administrator under Ronald Reagan. Under his directorship, the OMB's Office of Information and Regulatory Affairs was the gatekeeper for virtually all proposed regulations dealing with public health and safety. It quickly became known as a bureaucratic "black hole," where proposed regulations went in for review and never came out" (Weiss, 2004).

According to Weiss, Tozzi is extremely proud of his contribution in the fight against regulation.  Tozzi stated that "We sandwiched [the DQA] between Jerry Ford's library and something else...  Was it something that did not have hearings?  Yes.  Is it something that keeps me awake at night? No. Is it something that I would do again, exactly?  Yes, you bet your ass I would.  I would not even think about it, okay? Sometimes you get the monkey, and sometimes the monkey gets you" (2004).  Tozzi has also been credited with helping Phillip Morris discount evidence that suggested second-hand smoke was dangerous, that giving aspirin to children with flu symptoms contributed to the development of Reyes syndrome during the 80's, and using the DQA to discredit studies that found that the common pesticide Atrazine chemically castrated wild frogs, (Weiss, 2004).

Affected Data

The heart of the DQA is its ability to suppress the dissemination of information gathered by regulatory agencies.  "Some information disclosed by the government is objective, factual information generated by private parties or by the government itself....  Some is disseminated by the government results from testing and evaluation done by agencies or for agencies" (Shapiro, 2004, p. 341).

Shapiro (2004) argues that this disclosure and dissemination generally results in positive action.  First he states, when "individuals are aware of potential risks, they may be able to take protective actions" (p. 342).  Secondly, individuals may also use the additional information to further these and other goals of regulations, such as boycotting offending entities or engaging in "actions that reduce environmental risks" (p. 343).  All of which produce benefits to public well-being.

What the DQA requires is "that all federal agencies affected by the guidelines issue their own comprehensive guidelines `ensuring and maximizing' the quality of their data" (Lacko, 2004, p. 306).  Furthermore, it "directs agencies to establish administrative mechanisms that allow `affected' parties to seek and obtain correction of information when that information fails to meet the standards of the DQA" (p. 306).  Finally, the DQA requires that any such request for correction is to be reported directly to the Director of OMB.  Rena Steinzor (as cited by Weiss, 2004) claims that these requirements make the DQA is a "tool to clobber every effort to regulate... [and] amounts to censorship and harassment."

These guidelines, however, have been interpreted inconsistently since the inception of the law.  In an effort to clarify the requirements of DQA, the OMB issued guidelines in the interpretation of the law.  As established by Appendix A, OMB has stated specifically that these guidelines apply to information and dissemination as defined by the Paperwork Reduction Act.  Namely, that "information means any communication or representation of knowledge such as facts or data" and dissemination means "agency initiated or sponsored distribution of information to the public" (OMB Circular A-130).

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