Thursday, April 17, 2014
Alex Stein (Cardozo) recently posted “Inefficient Evidence” (forthcoming Alabama Law Review) to SSRN. The article offers a unifying theory of evidence that, in Stein’s view, justifies (at least to some degree) the American evidence rules. The key concept in this theory is the “signal to noise ratio” or SNR. Evidence whose significance to the case is difficult to evaluate has a low SNR (the signal is difficult to filter from the noise) and is, Stein argues, rightly excluded. Evidence that is more easily evaluated has a high SNR (its signal is easier to filter out from the noise) and should be admitted. The SNR ratio resonates with familiar Rule 403 conceptions, but Stein relies on it to explain evidence law more broadly, including the hearsay rules, the prohibition on character evidence, and more.
What I especially like about Stein’s piece is that although it sketches a very high-level theory of evidence, it nevertheless grapples with concrete examples, taking on discrete hearsay exceptions for example and explaining why they are (or are not) justified in light of SNR. Of course, this also makes his argument sufficiently tangible that it can be understood . . . and critiqued.
My initial reaction to the paper is that while elegant, it does not do as well a descriptive job as Stein suggests. For example, there are many examples of evidence that seem to fare poorly under SNR analysis, but are routinely admitted: e.g., stranger eyewitness identification testimony (as well as other broad swaths of live witness testimony), certain variations of forensic expert testimony, positive character evidence. Other evidence is routinely excluded that probably would fare well under SNR analysis, such as certain forms of propensity evidence (e.g., a driver’s history of drunk driving when sued for negligence) or hearsay statements of deceased victims. Of course, I may simply be intuiting the wrong SNR analysis for these forms of evidence, which gets to my second critique, which is that it seems difficult to discern the SNR of categories of evidence with any real precision.
These critiques are fairly mild given the ambitious scope of the piece, an article that, at a minimum, provides an interesting prism through which to evaluate evidence rules. It is also a refreshing challenge to the strong vein of Evidence scholarship that advocates doing away with limits on relevant evidence. For those reasons “Inefficient Evidence” is recommended reading.
Here is the abstract:
To operationalize this idea, I introduce a “signal-to-noise” method borrowed from statistics, science, and engineering. This method focuses on the range of probabilities to which evidence falling into a specified category gives rise. Specifically, it compares the average probability associated with the given evidence (the “signal”) with the margins on both sides (the “noise”). This comparison allows policymakers to determine the signal-to-noise ratio (SNR) for different categories of evidence. When the evidence’s signal overpowers the noise, the legal system should admit the evidence. Conversely, when the noise emanating from the evidence drowns the signal, the evidence is inefficient and should therefore be excluded. I call this set of rules “the SNR principle.” Descriptively, I demonstrate that this principle best explains the rules of admissibility and corroboration by which our system selects evidence for trials. Prescriptively, I argue that the SNR principle should guide the rules of evidence-selection and determine the scope of criminal defendants’ constitutional right to compulsory process."