Damages, Part I
Cases:
Harolds Stores, Inc. v. Dillard Department Stores,
82 F.3d 1533 (10th Cir. 1996)
Cimino v. Raymark Industries, Inc.
751 F.Supp. 649 (E.D.Tex.1990), rev’d, 151 F.3d 297 (5th Cir. 1998)
Harold’s v. Dillard’s
Facts:
Harold’s alleged that Dillard’s had infringed Harold’s
copyrighted fabric designs, violating federal and Oklahoman
law. Specifically, Harold’s alleged that from May 1993 to
August 1993, Dillard’s sold a number of skirts that appeared
identical to original print skirts that Harold’s had developed
and sold during the 1991-1992 season.
*Harold’s had sold the skirts at issue for $78 to $80
apiece; Dillard’s priced the ‘copycat’ skirts at $28 to $30.
*Two weeks after Harold’s filed its original complaint in
Oklahoma (on July 7th, 1993), Dillard’s reduced the price of
the skirts to $12 or $12.25, a 59% markdown that set the
price at below cost.
*On August 17th, 1993, Dillard’s agreed to stop selling
the print skirts in markets where Harold’s and Dillard’s
competed.
*During discovery, Harold’s learned that a Dillard’s
merchandise manager had instructed their suppliers to
manufacture skirts using Harold’s skirts as “inspiration.”
Another manager purchased Harold’s skirts so that Dillard’s
supplier could copy the print fabric designs and styles.
*Designers in the fashion industry commonly use other
manufacturer’s garments for inspiration. However, industry
practice requires that the derivative designs be sufficiently
different to avoid copyright infringement.
*Prior to trial, Dillard’s stipulated that it had infringed 19
of Harold’s copyrighted print fabrics. Dillard’s had offered
22,000 infringing garments for sale and had placed advance
orders for 15,000 more, for a total of 37,000.
*As Harold’s had only sold the skirts at issue during the
1991-92 season, they stipulated that Dillard’s 1993 copyright
infringement did not deprive Harold’s of any sales of the
copyrighted skirts. Instead, Harold’s claimed that Dillard’s acts
injured its reputation and goodwill, and damaged its relations
and future sales with present and prospective customers.
But how to prove damages?
Enter… the
unsinkable Dr.
Daniel Howard!
(of Kis v. Foto
Fantasy fame.)
Demonstrating Damages:
Dr. Howard’s “Shopping Survey”
To establish its damages, Harold’s relied
on Dr. Howard, who conducted a survey of
college-age women who had visited a
Dillard’s store during the relevant time
(May – August 1993) and who had visited a Harold’s
store or examined a Harold’s catalog in 1991 – 1992.
From the results, Dr. Howard calculated Harold’s
nationwide damages due to the copyright infringement.
Dillard’s objected to the survey because:
(1) it failed to survey a relevant universe
of consumers, and
(2) it was not material or probative to
establish copyright damages.
Applicable Rules and
Standards of Review
Survey evidence is admissible if it is
“material, more probative on the issue than
other evidence and if it has guarantees of
trustworthiness.”
“The survey should sample an adequate or
proper universe of respondents” and
should be excluded “when the sample is
clearly not representative of the universe it
is intended to reflect.”
The district court’s admission of a survey is
reviewed for “an abuse of discretion.”
Dr. Harold’s Survey Instrument
Instructions: Please respond to the following questions by placing a "x" in the space
that most closely reflects your memories and your feelings about the issues addressed.
(1) Have you visited a Harold's store or looked at a Harold's catalog in the past two
years (in 1991 or 1992)?
___yes ___no ___unsure
(2) Did you visit a Dillard's department store from May to August of this year (1993)?
___yes ___no ___unsure
CONTINUE THE SURVEY ONLY IF YOU ANSWERED "YES" TO #1 AND #2
(3) On any of your recent visits to Dillard's, have you seen any print skirts with patterns
you thought of as being unique to Harold's?
___yes ___no ___unsure
(4) On any of your recent visits to Dillard's, have you seen any women's purses with
designs you thought of as being unique to Harold's?
___yes ___no ___unsure
(5) How likely or unlikely is it that you will purchase clothes from Harold's within the
next year?
very likely ___:___:___:___:___:___:___ very unlikely
(6) Is this the first time you have answered these questions?
___yes ___no ___unsure
The Survey – Sampling Frame
Dr. Howard sampled undergraduate women from
Southern Methodist University (SMU) in Dallas,
Texas.
A total of 1,231 surveys were collected,
representing 44.3% of the undergraduate female
population.
27 individuals indicated they had answered the
questions previously, leaving 1,204 surveys.
578 respondents answered yes to questions 1 and
2, placing them in the relevant sample universe.
2 of these were eliminated for failing to complete
the survey, leaving a final sample of 576.
No incentives were offered for participation.
Dr. Harold on Appropriateness of
Sample
“This analyst sees no reason to
expect the responses of women in
Oklahoma to systematically vary from
those in Dallas Texas.”
“Undergraduate women were utilized
for study purposes since they are an
important market segment for both
Harold’s stores and Dillard’s.”
Survey Sample – Critique
Strengths
-Large Sample size
-Sample generally related to Harold’s core customer base (at
least according to testimony)
Weaknesses
-Geographic variation (Dallas v. Oklahoma v. Nation)
-Possible anomalies related to the Dillard’s/Harold’s
serving SMU campus (Highland Park Village v. Northpark
Mall)
-Undergrads only
-Women only
-SMU only
Survey Sample - Suggestions
Stratification and (if necessary) weighting
of sample to reflect the full proportions of
Harold’s clientele
Greater recognition of relevant sample
variables (income, age, sex, education,
etc.)
If fiscally possible, cluster sampling of
varying geographic locations would better
support an inference concerning Harold’s
national injury.
The Survey Instrument –
Measurement and Methodology
Questions 1 and 2 – establishing a relevant
sample of respondents potentially exposed to
Harold’s skirts and Dillard’s copycat skirts.
Question 3 – Identifying respondents who had
seen skirts at Dillard’s with patterns they believed
unique to Harolds.
Question 4 – “purse” question – asked to eliminate
“yes-saying bias” and other error.
Question 5 – Scale to determine likelihood of
buying from Harold’s – meant to measure the
influence of the Dillard’s skirts on future purchase
behavior.
Question 6 – To eliminate repeat players.
Measurement & Method – A critique
Questions 1 and 2: Visiting is not
equal to shopping/purchasing
Question 3: Insufficient to indicate
exposure to the skirts at issue.
-A search for ‘skirts’ Harold’s website today
brings up 56 hits; on Dillard’s website, 583.
Question 4: A “purse” differs from a
“skirt” in important ways, making it a
less effective means of eliminating
unreliable respondents.
Question 5: This “Likert-type” question allows for relative
intentions of the skirt ‘exposed’ and ‘non-exposed’ groups.
However, the use of this single question allows for
errors often found in “natural” experiments and “static-group
comparisons.”
Sources of internal invalidity:
*Testing – Might their answer to this question
change after being reminded of Harold’s non-uniqueness in
question 3?
*Selection Bias – Is exposure really the only
difference between the two groups?
Other Concerns:
*Construct Validity – Does the answer to
question 5 really tell you about the effect the “copycat” skirts
had on the respondents?
Measure/Method - Suggestions
Ask if the respondent has shopped or bought clothing from Harold’s
before.
For those who said “yes” to question 3, once they’ve completed the
rest of the questions ask them to identify the skirt(s) they were
exposed to from a photo array of infringing/noninfringing skirts.
Use “pants” or “tops” rather than “purses” for question 4.
Have respondents answer question 5 first to avoid testing invalidity
problems.
Test reliability by delivering the survey again at another location.
Include questions more specific to the connection between
exposure to the copycat skirts and a decreased likelihood to shop
at Harold’s:
-Is any hesitation over shopping at Harold’s due to price?
Quality of clothing? Style?
-Has their inclination to shop at Harold’s increased, decreased
or stayed the same over the past 6 months? Two years?
-Could possibly include open ended questions (similar to
those in the Jay report from Napster) asking why a respondent may
be reluctant to shop at Harold’s – the results may not be particularly
probative but may provide a source of external validation.
Survey – Results
Purses
Yes
No
Unsure
Row
Total
Yes
48
(8.3%)
66
(11.5%)
46
(8.0%)
160
(27.8%)
No
12
(2.1%)
141
(24.5%)
37
(8.0%)
190
(33.0%)
Unsure
20
(3.5%)
27
(4.7%)
179
(31.1%)
226
(39.2%)
Column
Total
80
(13.9%)
234
(40.6%)
262
(45.5%)
576
(100%)
Skirts
(X2 = 235.01; p < 0.00001)
Mean Scores on Intentions to
Purchase Clothes from Harold’s
within the Next Year
Purses
Skirts
Yes
No
Unsure
Yes
5.60
N = 48
3.18
N = 66
5.17
N = 46
No
3.92
N = 12
4.75
N = 141
4.97
N = 37
Unsure
4.90
N = 20
4.26
N = 27
4.44
N = 179
Conclusions – Damage Calculation
The survey showed 27.8% (N = 160) of respondents
identifying Dillard’s skirts as having patterns unique to
Harold’s.
Of these, 8.3% said “yes” to purses and 8.0% said “unsure”
to purses. Eliminating these leaves 11.5% (N = 66).
For those who did not see unique skirts nor purpose, their
mean likelihood to shop at Harold’s was 4.75. For those who
saw the unique skirts but did not see the purses, their mean
was 3.18.
The difference between these means is 1.57, or 33.1%.
Thus, Dr. Howard found the skirts lead to a 33.1% reduction
in a respondent's intention to visit Harolds.
Drawing on several trade journals, Dr. Howard extrapolates a
.341 multiplier to estimate the likely relationship between the
decrease in purchase intent and a decrease in purchase
behavior. He concludes that the actual reduction in
purchasing behavior will be slightly more than 11 percent.
(0.331 x 0.341 = 0.113)
Damage Calculation - Continued
From there, Dr. Howard basically utilizes a series
of attenuated assumptions to calculate damages.
For example,
*Based on a national study that reported 55%
of men’s apparel was bought by women, the same
proportion was assumed for Harold’s.
*The survey above shows that 44% of men’s
apparel nationally is purchased by men. Based on
a telephone survey of 100 SMU males, Dr.
Howard found that 48.6% of a man’s expenditures
on men’s clothing was influenced by advice from
women. Thus, an additional 21.4% (.486 x .44) of
men’s apparel purchases nationally (and
presumably in Harold’s) are influenced by women.
*Thus, 76.4% (55.0% + 21.4%) of men’s
clothing at Harold’s is potentially affected by
Dillard’s skirt copying.
Wrap-up
The Court finds that the
shopping survey was properly
admitted. It concludes that
“there was substantial evidence
tending to support the jury’s
damage award” of
$312,000.00.
Do you agree?
Cimino v. Raymark Industries
“I view your role as one of the commanding
generals. You are the Eisenhower of this D-Day
operation. The rest of us are colonels prepared to
take orders in this joint effort… The magnitude of
this assignment is unprecedented in federal court
history…”
-Judge Robert Parker, who presided
over Cimino in the Eastern District of Texas, encouraging
Judge Charles R. Weiner of the Eastern District of
Pennsylvania. Two days earlier, the full asbestos caseloads
of eight federal district judges had been transferred to
Weiner’s court in a mass consolidation effort.
“Many Mistakes and Missed Opportunities” The Asbestos Crisis Leading up to Cimino
1981: Forty-Eight Insulations seeks discovery to help establish
a district wide market share determination among the
defendants.
-Forty-Eight Insulations abandoned its motion
under pressure from its co-defendants. The Texas district
court failed to press the issue.
1981: The district court used issue preclusion to declare
asbestos containing products unreasonably dangerous as a
matter of law, and further precluded plaintiffs from seeking
punitive damages.
-In Hardy v. Johns-Manville Sales Corp., 681
th
F.2d 334 (5 Cir. 1982) the Court of Appeals rejected the
approach.
Mid-80s: The district court established a voluntary ADR
program. Most defendants elected to participate and a
number of settlements ensued.
-The ADR program was set aside by the
Eastern District Sitting en banc.
1986: In Jenkins v. Raymark Industries, Inc., 782
F.2d 468 (5th Cir. 1986), the 5th Circuit approved of
Judge Parker’s certification of a class of 900
asbestos claimants for certain common questions.
-After that order and certain
settlements, 3,031 asbestos personal injury cases
accumulated in the Eastern District of Texas.
1989: Judge Parker attempts to consolidate the
2,990 Cimino class members into a single group,
represented the full trials of the 11 class
representatives plus 30 “illustrative” cases – 15
chosen by the defendant and 15 by the plaintiff.
-The plan was rejected by the Court of
Appeals in In re Fibreboard Corp., 893 F.2d 706
(5th Cir. 1990).
As a result of delays and difficulties, as of 1990:
*448 class member died waiting for their cases to be
heard
*$.61 of every asbestos-litigation dollar went to
transaction costs.
*Raymark, Forty-Eight Insulations, Unarco, Standard
Asbestos, Johns-Manville, Eagle Picker, and Celotex
were bankrupt.
*Federal asbestos filings averaged 1,140 per month.
*For every case resolved, two new ones were filed.
Judge Parker notes in the introduction of Cimino, “If the
court could somehow close thirty cases a month, it
would take six and one-half years to try these cases
and there would be pending over 5,000 untouched
cases at the present rate of filing.”
So Why do you Care?
When analyzing Judge Parker’s trial plan
for Cimino, it pays to keep the asbestos
context in mind.
As Saks & Blank note in Justice Improved,
when responding to the objection that
aggregation denies parties procedural
justice,
one answer comes from asking the
question,
“Compared to what?”
Cimino v. Raymark – The Plan
The class consisted of 2,298 plaintiffs claiming asbestosrelated injury or disease resulting from exposure to defendants’
asbestos-containing insulation products. These plaintiffs went
to trial against Pittsburgh-Corning, Fibreboard, Celotex, CareyCanada, and ACL. The trial plan consisted of three phases:
Phase I: A complete jury trial of the entire cases for the nine class
representatives and a class-wide determination of issues of
product defectiveness, warning, state of the art defense and
fiber type defense. The jury also assessed a punitive damages
multiplier for each defendant “for each $1.00 of actual
damages” as follows:
Carey-Canada…..$1.50
Fibreboard……….$1.50
Celotex……………...$2.00
Pittsburgh-Corning...$3.00
These procedures were approved of in Jenkins by the
Court of Appeals.
ACL was granted a nonjury trial pursuant to the foreign
sovereign immunities act.
Phase II: This phase required a jury finding for each of the
worksites, crafts, and relevant time periods as to whether
asbestos-containing insulation products were used, as well as
which groups were sufficiently exposed to such asbestos
products to cause the alleged injuries. Finally, an
apportionment of causation was made among defendants,
settling and non-settling.
In the actual trial, Phase II was dispensed with on the
basis of a stipulation amongst the parties.
(On appeal, the 5th Circuit found the trial plan violated
defendants’ Seventh Amendment rights. They noted that “under
Texas law causation must be determined as to ‘individuals, not
groups.’ And, the Seventh Amendment gives the right to a jury
trial to make that determination.” The Court based this result on
the Erie doctrine – requiring Texas substantive law to apply -and Congress’ failure to act.
On the other hand, in his concurrence Judge Garza
suggested that “Judge Parker’s phase II plan would have been
sufficient if he had implemented the plan rather than disposing
of it with the phase II stipulation.”)
Phase III: DAMAGES
All Cimino plaintiffs waived their right to an individualized
verdict and agreed to the Phase III procedure. The 2,298 class
members were stratified into five disease categories based on
the plaintiffs’ injury claims. A random sample was selected from
each category as follows:
Sample Size
Disease Category
Population
Mesothelioma
15
32
Lung Cancer
25
186
Other Cancer
20
58
Asbestosis
50
1050
Pleural Disease
50
972
TOTALS
160
2298
Calculation of Damages:
*Two juries were utilized to hear the randomly
selected 160 sample cases. Each plaintiff selected
was awarded his individual verdict. Afterwards, the
non-sample plaintiffs were each awarded the
average verdict of all the samples within their
disease category.
*The defendants were not allowed to present
evidence on causation but were permitted to present
evidence of contributory evidence, such as smoking.
*The Court ordered remittiturs in thirty-four of
the pulmonary and pleural cases and in one
mesothelioma case.***
*Zero verdicts were also factored into the
damages awarded to nonsample plaintiffs.
***Note: Pleural Disease is the least serious of the disease
classifications; yet the average pleural disease award
exceeded that of asbestosis and lung cancer by more than
$10,000, even with the remittiturs and zero verdicts.
Phase III – Statistical Analysis
The defendants argued that aggregate valuation
was inappropriate for mass tort cases. Judge
Parker responded first by pointing out the
defendants’ hypocrisy, given their own reliance on
statistics during the trial.
In support of his use of statistics, Judge Parker
quotes the 6th Circuit Court of Appeals in E.K.
Hardison Seed Co. v. Jones, 149 F.2d 252, 256
(6th Cir. 1945), “The prerequisites necessary to the
admission in evidence of samples are that the
mass should be substantially uniform with
reference to the quality in question and that the
sample portion should be of such nature as to be
fairly representative.
The 99% Confidence Interval
After the 160 verdicts were rendered, Judge Parker held a
post-trial hearing to evaluate the representativeness of the
sample cases.
The Court sought a confidence level of 95% (+/- 2 standard
deviations).
The plaintiff’s statistical expert, Dr. Frankiewicz, examined
the “goodness-of-fit” between the samples and the disease
categories, considering a range of variables relevant to
causation and the category population.
Dr. Frankiewicz determined that, with two minor exceptions,
the samples on a whole achieved a 99% confidence level, or
a standard deviation of +/- 2.56.
The Court declared that the actual precision level of the
samples “exceed[ed] that sought by the Court.”
How confident are you in this analysis?
Confidence Level v. Interval
“All statements of accuracy in sampling must specify both
a confidence level and a confidence interval.”
-Course materials, Chapter 7, “The Logic of Sampling,” p. 204.
For example, a Gallup poll may tell us, “One can say with
95% confidence that the margin of sampling error is ±3
percentage points.” This means that 19 times out of 20
(confidence level), the poll will be within 3 percentage
points of the actual public opinion (confidence interval).
Cimino gives us the confidence level while failing to
specify the confidence interval – a wide confidence range
(like a range of +/- 25 percentage points in a poll) could
lead one to doubt how representative the sample cases
really are.
Still, given the number of samples taken of each disease
category, if the population resembles a normal bell curve
the standard deviation from the mean is unlikely to be
large… though it may still be significant.
Hypothetical Standard Errors
Hypothetical
Standard Error*
based on
Gender**
Hypothetical
Standard Error*
based on
Worksite***
Sample
Size
Disease
Category
Population
Mesothelioma
15
32
6.85%
3.06%
Lung Cancer
25
186
8.66%
3.87%
Other Cancer
20
58
7.33%
3.27%
Asbestosis
50
1050
6.73%
3.01%
Pleural Disease
50
972
6.71%
3.00%
TOTAL
160
2298
*Standard Error = square root of (product of population parameters [P x Q] divided
by sample size [n]). As each sample size is around 5% or more of the actual
population, we must multiply the error rate above by a "finite populational correction"
(1 - proportion of population) to achieve the true standard error.
**Presuming 50% of population of Plaintiffs is female. (Note: This was likely
not the case in Cimino.)
***Assuming that each of the 19 worksites was represented in equal proportion by
the plaintiff population -- in other words, that 5.26% of the plaintiffs came from any
one worksite. (Note: This was likely not the case in Cimino.
Aggregating Well: Tips from Saks and Blanck
Representativeness is the touchstone of good
sampling.
*When measuring the representativeness of
your sample, set your p-level high.
-Conventional significance testing (with plevels of .01 or .05) aims to be conservative about
erroneous rejection of the null hypothesis, i.e.,
making it hard to find a significant difference.
-In sampling from known aggregations,
the reverse is true: we want to guard against
erroneously concluding that the sample equals the
population mean. Thus, we want to make it easier to
reject the null hypothesis. This can be done by
setting the p-level for the proposed significance tests
at .20 or higher.
*Remember that representative samples may
become less so over time (for ex., as plaintiffs die off
or are added.)
*Draw enough samples to satisfy legal standards.
Achieve within-group Homogeneity and BetweenGroup Heterogeneity
*Stratify: Using the 5 disease groups in Cimino
helped ensure adequate representation of each group
and created more homogenous subpopulations.
*Use data from past jury awards to determine
which variables were important -- these can be used to
form subgroups
*Using cluster analysis on data describing the
case population can help to maximize between-group
heterogeneity and within-group homogeneity.
Due Process – the Legal Standard
Perhaps the greatest hurdle faced by
aggregative sampling is legal
xenophobia – as in the strict
adherence to a “traditional” form of
due process.
Principles of Due Process are
embodied by the Matthews Test, as
well as instrumental and
noninstrumental values.
Due Process – Matthews Test
In Matthews v. Eldridge, the Supreme Court
identified 3 factors that shape the due process
balancing test:
(1) The private interest of the defendant affected,
(2) The risk of erroneous deprivation of interest
through the procedures used, and
(3) The Government’s interest, including all fiscal
and administrative burdens that the additional
procedure would require.
*In suits involving private parties, the Court in
Connecticut v. Doher modified the third prong to
focus on the private interest of the plaintiff, with
the Government’s interest as an ancillary
concern.
Matthews Test – Applied to Cimino
(1) Defendants face a minimal reduction in control
and in appearance of due process; they will
likely pay about the same damages while saving
significant transaction costs.
(2) For the defendants, little risk of erroneous
deprivation.
(3) The plaintiffs may face the prospect of having no
recovery, being forced to settle or dying before
their case comes to judgment. Government has
a strong interest in streamlining the asbestoslitigation process.
Due Process – Noninstrumental
Values
“Appearance” of Justice
Equality before the Law
Predictability
Transparency
Rationality
Participation
Revelation
Aggregation and Noninstrumental
Values
Saks and Blanck suggest that nearly all
noninstrumental values are equally, if not better
supported by the aggregation procedure.
The one possible exception is that of the
“appearance” of justice – that aggregation denies
procedural justice.
In response, Saks and Blanck point out that
Aggregation has never been compared empirically with
traditional procedures.
While aggregation may give defendants more limited
process, it won’t shut them out of trial opportunities
altogether. In contrast, a plaintiff’s only real shot at having
their day in court may be vicariously through aggregation
and sampling. Thus, aggregation may afford the most
procedural justice under the circumstances.
Due Process – Instrumental Values
The major instrumental value is
*Accuracy – the right to notice, hearing,
and counsel each contribute to a more
accurate process. A fair process ought to
result in plaintiffs receiving, within
reasonable tolerances, the proper amount
in damages. The process should lead to
rational, reasonably accurate, and nonarbitrary outcomes.
Aggregation – A stronger path to
Instrumental Accuracy
Utilizing an array of damage awards, the
‘aggregate’ award is more likely to come
near the ‘true’ or ‘correct’ damage measure
than a single verdict.
Aggregation will refine out some of the
random and systematic error (ex.
Irrationality and bias) of jury decisions,
while preserving the core of the jury’s logic.
Accuracy is unlikely to be a problem for
defendants with any reasonably done
aggregation procedure.
Seventh Amendment - Juries
Given the disparity between the two
juries in the Cimino case, a larger
number of juries may be preferable.
Still, like any other sample, we need
not use a jury for every single case to
achieve reliability.
When using multiple juries, the cases
should be assigned randomly.
A quick note on Plaintiffs v. Defendants
Interestingly, though the defendants were the
ones to protest in the Cimino case,
aggregate procedure is much more likely to
award an inappropriate amount to a plaintiff
than to charge an inappropriate amount to a
defendant.
Ex. In Cimino, nonsample plaintiffs who did not
smoke still had their awards reduced by any
contributory negligence found against a sample
plaintiff who smoked.
This anti-plaintiff bias leads some to suggest that
while it is reasonable to mandate that defendants
submit to aggregate procedure, it is not
reasonable to force plaintiffs to do so, unless the
risks can somehow be shifted to the defendant.
Alternative I – Abraham/Robinson
Aggregative Valuation
In “Collective Justice in Tort Law,” Profs. Abraham
and Robinson propose compiling a statistical
model for determining individual claims:
Baseline appraisals of the value of individual claims
would be set by using statistical claim profiles, or models.
The profiles would indicate the amounts paid in judgment
or settlement to claimants falling into different categories.
These categories would be defined as functions of
variables that affect liability and the severity or duration of
plaintiff’s illness.
Claim valuation would be a function of probability and
magnitude of payout.
Thus, the estimated parameters could be used to
calculate damage awards for untried cases.
Alternative II - the “Plaintiffs Cut, Defendant
Chooses” Model
Seeking to deal with aggregation’s tendency to place the full
burden of precision on plaintiffs, David Friedman has
hypothesized an “Incentive-Compatible” Procedure for litigating
mass torts:
(1) Attorney for N plaintiffs produces, for each plaintiff i, a
claim C[i], which is the amount the attorney claims that
plaintiff i aught to receive in damages.
(2) Plaintiff gives list of claims C[i] to defendant’s attorney.
(3) Defendant’s attorney selects a small number (say, 10) of
cases to be tried. (We’ll call these plaintiffs 1-10.)
(4) These cases are tried. The court awards damages D[i] to
each of the 10 plaintiffs.
(5) The court calculates R = (D[1]/C[1] + D[2]/C[2] +…+
D[10]/C[10])/10, and awards damages of R x C[i] to each of
the N plaintiffs.
Under this system, the plaintiffs’ attorney will have incentive to
make each claim reasonably proportional to actual
damages. (Do you see why?)
Friedman suggests several variations on this model to control
for cost and errors.