Cordelia's Dilemma
Silence, though usually undervalued, can be golden
by Stephen Jay Gould
While Goneril and Regan jockey for their father's wealth by proclaiming
their love for him in false and fulsome tones, Lear's third daughter,
Cordelia, fears the accounting that her father will soon demand: "What
shall Cordelia do? Love, and be silent...since, I am sure, my love's more
ponderous than my tongue."
Lear then forces Cordelia into this game of ever more elaborate professions
of love: "What can you say to draw a third more opulent than your
sisters?" When the honorable Cordelia, refusing to play falsely for
gain, says nothing, Lear cuts her off from all inheritance, proclaiming
that "nothing will come of nothing."
Lear's tragic error, which shall lead to blinding, madness, and death,
lies in not recognizing that silence--overt nothing--can embody
the deepest and most important meaning of all. What, in all our history
and literature, has been more eloquent than the silence of Jesus before
Pilate, or Saint Thomas More's date with the headsman because he acknowledged
that fealty forbade criticism of Henry VIII's marriage to Anne Boleyn,
but maintained, literally to the death, his right to remain silent and
not to approve?
The importance of negative results--nature's apparent silence or
nonacquiescence to our expectations--is also a major concern in science.
Of course, scientists acknowledge the vitality of a negative outcome and
often try to generate such a result actively--as in trying to disprove
a colleague's favored hypothesis. But the prevalence of negative results
does pose an enormous, and largely unaddressed, problem in the reporting
of scientific information. I do not speak of fraud, cover-up, finagling,
or any other manifestation of pathological science (although such phenomena
exist at a frequency that, in all honesty, we just do not know). I refer,
rather, to the all too wonderfully human love of a good tale--and
to our simple and utterly reasonable tendency to shun the inconclusive
and the boring.
The great bulk of daily scientific work never sees the light of a published
day (and who would wish for changes here, as the ever-increasing glut
of journals makes keeping up in one's own field impossible and exploration
of others inconceivable?). Truly false starts are deposited in circular
files--fair enough. But experiments fully carried forth and leading
to negative results end up, all too often, unpublished in manila folders
within steel-drawer flies, known only to those who did the work and quickly
forgotten even by them. We all know that thousands of novels, considered
substandard by their authors, lie in drawers throughout the world. Do
we also understand that even more experiments with negative results fill
scientific cabinets?
Positive results, on the other hand, tell interesting stories and are
usually written up for publication. Consequently, the available literature
may present a strongly biased impression of efficacy and achieved understanding.
Such biases, produced by the underreporting of negative results, do not
only permeate the arcana and abstractions of academic science. Serious,
even tragic, practical consequences often ensue. For example, spectacular
medical claims for the efficacy of certain treatments (particularly for
chronic and fatal illnesses like cancer and AIDS) may be promulgated after
a single positive result (often obtained in a study based upon a very
small sample). Later and larger studies may all fail to duplicate the
positive results, effectively disproving the value of the treatment. But
these subsequent negative results often appear only in highly technical
journals read by more restricted audiences and, as nonstories, do not
so readily attract the attention of the media--and people may continue
to squander hope and waste precious time following useless procedures.
Statistics often get a bum rap in our epithets and editorials. But I
am both a champion and a frequent user of statistical procedures, for
the science exists largely to identify and root out hopes and misperceptions
falsely read into numerical data. Statistics can tell us when published
numbers truly point to the probability of a negative result, even though
we, in our hopes, have mistakenly conferred a positive interpretation.
But statistics cannot rescue us when we hide our nonlights under a bushel
(with apologies to Matthew 5:15)--that is, when we only publish positive
results and consign our probable negativities to nonscrutiny in our file
drawers.
I had thought about this problem a great deal (especially when writing
The Mis-measure of Man), but I had not realized that this special
sort of bias had both a name and a small literature devoted to its weighty
problems, until I came upon a paper by Colin B. Begg and Jesse A. Berlin
entitled "Publication bias: a problem in interpreting medical data"
(Journal of the Royal Statistical Society, vol. 151, 1988, pp.
419-63).
Begg and Berlin begin their paper with a wonderful quotation from Sir
Francis
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