Laura Greenberg*

Abstract:  Traditional determinations of tort damages disadvantage plaintiffs in lead paint litigation. When courts rely heavily on race-based statistics and closely scrutinize the achievements of the plaintiff’s family, low-income and minority plaintiffs suffer the immediate consequences. This method of compensation reinforces the notion that the tort system reflects the realities of current economics, complete with all its inequities. As this Note suggests, however, the tort system should strive to mitigate these discriminatory realities rather than remaining complacent and content with the status quo. Adopting race-neutral statistics and comprehending the psychological theory of resiliency will allow courts to begin the damage calculation from a more optimistic and less discriminatory perspective.


Lead poisoning generally affects young children from low-income and minority families.1 It causes a variety of physical and psychological injuries, ranging from attention deficit disorder to mental retardation to kidney failure.2 Injured plaintiffs have successfully sued landlords and governmental agencies to recover for these injuries.3 Their compensation in such suits is measured, in large part, by the [*PG430]calculation of their loss of earning capacity.4 Typically, economists and rehabilitation experts rely on both race-based statistics and examinations of the vocational and educational achievements of the plaintiff’s family to determine the loss of earning capacity.5

Lead paint plaintiffs—young, poor and often African-American or Hispanic—are disadvantaged by the traditional determinations of loss of earning capacity.6 Using race-based statistics reinforces the current racial discrimination in the work force, ignoring the possibility and the social value of upward mobility.7 In addition, dependence on race-based statistics assumes that race is and should be the primary determinant of individual achievement.8 Focusing on the plaintiff’s family is also problematic for poor minority plaintiffs because it assumes that racism and classism will exhaust their opportunities in the same way that it may have adversely affected their relatives.9 In short, traditional determinations of loss of earning capacity presuppose that the legal system’s function is to reflect the disturbing status quo of discrimination.10

This Note advocates two proposals for combating discriminatory damage awards for lead paint plaintiffs. First, courts should adopt race-neutral statistics to make economic predictions about a child-plaintiff’s loss of earning capacity.11 Second, courts should become familiar with the psychological theory of resiliency.12 This theory identifies certain “protective” factors within children and in their en[*PG431]vironment that increase the likelihood of overcoming adverse situations such as poverty or racial discrimination.13 On a practical level, resiliency theory encourages experts to broaden the sources for their predictions of future earning capacity.14 In addition, resiliency theory has two theoretical consequences for damage awards: it emphasizes the speculative nature of predictions about what or who a child could become,15 and it suggests that experts should start from the optimistic assumption that children are, in fact, able to overcome adverse obstacles that confront them.16

Section I identifies the lead-poisoned population and clarifies the physical and psychological consequences of lead poisoning. Section II examines monetary damages in lead paint litigation, starting with the general method of calculation for adults and then focusing on the special case of the child-plaintiff. Section III emphasizes the problems that the traditional method of damage calculation poses for lead paint plaintiffs. Finally, Section IV advocates two proposals to help mitigate the discrimination in damage awards for lead paint plaintiffs: the adoption of race-neutral statistics and the integration of resiliency theory into damage determinations.

I.  Effects of Lead Paint Poisoning

Lead paint poisoning, while dangerous for everyone, tends to manifest itself primarily in young children.17 Not only are young children more likely than adults to ingest lead paint,18 but children’s bodies are particularly susceptible—biologically and developmentally—to the effects of lead paint.19 The poisoned population has other defining characteristics, namely that the young children are generally [*PG432]members of minorities from low-income families.20 Such families often occupy the older, deteriorating urban housing where lead paint remains prevalent. Their children have high risks of exposure to lead paint, especially since the severity of the physical and psychological effects of lead paint depends on the amount of lead paint ingested.21

A.  The Poisoned Population

1.  Young Children

According to the Center for Disease Control (CDC), a person’s blood lead level is at a dangerous level when it rises above ten micrograms per deciliter (10 mg/dL).22 This estimate applies to children and adults alike, although it is clear that children under five years of age tend to be especially susceptible to lead poisoning.23 Children’s bodies absorb and retain more lead than adults’ bodies, due in part to the likelihood of an iron deficiency which greatly increases the risk of absorption of lead into the gastrointestinal tract.24 Because children’s bodies and organs are in the developmental stage, even the slightest amount of lead can have a profoundly detrimental effect.25 For children under the age of three, the incomplete development of the blood-brain barrier increases the risk that lead will seep into the nervous system.26 Also, very young children are more likely than adults to ingest paint chips or paint dust because they are especially prone to hand-to-mouth contact.27

2.  Low-income and Minority Children

Housing conditions in the United States create another characteristic of the poisoned population: lead poisoned children tend to be [*PG433]members of minorities and low-income families.28 Since over 80% of houses built before 1978 contain lead-based paint, families who live in older, deteriorating housing have a higher risk of exposure than families in the newer communities.29 In addition, urban housing is more likely than suburban housing to contain lead paint.30 As low-income and minority families are more likely than white families to live in older, lower-income, inner city housing,31 it should come as no surprise that the majority of the poisoned population are poor African-American and Hispanic children.32

The CDC’s ranking of populations at risk for lead poisoning reflects this expectation, placing poor children and minority children at the top of the list.33 Other studies also acknowledge the identity of the poisoned population.34 For instance, a New York City study conducted in 1984 found that African-American children accounted for an estimated 60% of children living in standard metropolitan statistical areas with blood-lead levels greater than 25 mg/dL.35 A few years later, a similar study conducted by the Agency for Toxic Substances and Disease Registry (ATSDR) surveyed families throughout the United States who were significantly below the poverty line and found [*PG434]that, of that group, 68% of children with blood-lead levels above 15 mg/dL were black and only 36% of the children were white.36 The 1988 ATSDR study also showed that 26.6% of African-American children in the United States had blood-lead levels above fifteen mg/dL, whereas only 7.1% of white children had such elevated levels.37 Then, in 1997, a press release from the CDC noted that despite a dramatic decrease in blood-lead levels for all Americans, children from low-income families still exhibited higher levels than other children.38

The correlation between race, income, and lead poisoning might become even more pronounced in the near future.39 Until recently, the general public was exposed to lead through the use of leaded gasoline. Now, with increasing restrictions on leaded gasoline, lead exposure comes primarily from lead paint.40 Given the fact that low-income and minority families are more likely to occupy older houses with lead-based paint,41 “race and income will become better indicators of the likelihood of exposure to leaded paint, and, consequently, elevated blood lead levels.”42

B.  Physical and Psychological Consequences of Lead Poisoning

Lead poisoning affects children in a myriad of ways depending on the extent of the exposure.43 Typically, upon entering the body, lead concentrates primarily in the blood, soft tissue (such as the kidneys, bone marrow, liver, and brain), and mineralizing tissue (such as the bones and the teeth).44 High levels of exposure can cause kidney failure and brain swelling that can lead to coma or death.45 High exposure can also result in neurological damage, mental retardation, [*PG435]cerebral palsy, seizures, and behavioral problems.46 Lower levels of exposure can cause reduced IQ, cognitive difficulties, deficits in speech and language processing, attention deficit disorder, and full or partial hearing loss.47

Although science and legislation have made significant strides towards managing the causes and effects of lead poisoning in recent decades, there has been an explosion of lead paint cases brought against landlords or governmental housing agencies.48 This article focuses on the last stage of this complicated litigation process: the determination of damages.

II.  Damages in Lead Paint Litigation

The determination that a defendant is liable, which is often considered the final chapter of the litigation, is merely the beginning of the story for lead paint plaintiffs.49 Upon issuing a finding of liability, the court must quantify and redress the damages caused by the defendant’s conduct.50 For the purposes of the damages analysis below, the reader should assume that the plaintiff has successfully sued the defendant either in negligence or under a state or federal statute.51

A.Possible Types of Damages and the Negative Results for Minority Plaintiffs

The successful plaintiff is entitled to all the typical types of tort damages, including medical costs, pain and suffering, interruption of ordinary daily life, and loss of future earning capacity.52 As the number of toxic tort cases have increased in both complexity and number over the past few decades,53 tort attorneys have also begun to suggest non-traditional damages, such as recovery for future medical testing to detect diseases related to the exposure, for increased risk of related [*PG436]diseases, for fear of future related diseases, and for a variety of other emotional damages.54 In addition, courts often allow punitive damages.55 The goal of these damages is to put the plaintiff “in the same . . . position [economic or non-economic] as he or she would have occupied had he or she not been injured.”56

Not surprisingly, juries and judges treat minority plaintiffs differently from white plaintiffs when awarding any type of damages.57 The Rand Corporation and the Institute for Civil Justice studied jury trials from 1960 to 1979 in Cook County, Illinois, and concluded that compensation for white plaintiffs was 25% greater than compensation for black plaintiffs in the same situations.58 Thirty-eight percent of civil litigators surveyed in a 1991 New York study noted that white plaintiffs received more relief than minority plaintiffs on a regular basis.59 Similarly, 45% of respondents in an Oregon study (and 60% of minority respondents) concluded that juries are likely to award less compensation to minority litigants than to white litigants.60

According to Professor Martha Chamallas, one of the explanations behind lower damage awards is that the tort system consistently devalues the potential of minority plaintiffs.61 Basic legal categories, such as damages, are infused with racial biases.62 This devaluation is particularly harmful in calculations of loss of earning capacity, where experts rely heavily on race-based statistics to determine the plaintiff’s value.63

[*PG437]B.  Loss of Earning Potential

1.  Significance and Definition

Tort plaintiffs frequently focus on loss of earning capacity as the heart of their request for damages.64 For many tort cases, and particularly for lead paint cases, loss of earning potential is the “‘big ticket’ item of damages, which can make the difference between a modest and sizable award.”65 In Floyd v. Fruit Industries, for example, the Connecticut Supreme Court noted that for a plaintiff who had an appreciable income before the accident or who was steadily employed, “the destruction of earning capacity may well be the principal element of recovery. . . .”66 Loss of earning capacity also has a conceptual significance: as a measure of human potential, it reflects societal judgments about the worth of the plaintiff as well as the groups to which the plaintiff belongs.67

In general, damages for loss of earning potential (also called loss of earning capacity) represent the difference between the plaintiff’s potential to earn before and after the accident, which, in a simple case, is equal to the actual earned wages before the accident plus a calculation that takes into account the possibility of upward mobility.68 As with all calculations of future damages, loss of earning potential must be reduced to net present value

to establish a level of compensation which recognizes that an individual could invest a present amount today in an interest-earning asset and use the interest generated . . . together with a gradual withdrawal of the principal to compensate [*PG438]fully for the damages sustained as a result of the loss of future earning capacity. . . . 69

2.  Calculating Loss of Earning Capacity for an Adult

Predicting future damages is, by its very nature, speculative.70 Particularly in the case of lost earning capacity, the fact-finder may exercise broad discretion in calculating the exact figure.71 The most successful plaintiffs, however, rely on economists and rehabilitation experts who assess productivity, average earnings for the pre-accident vocation, growth trends in wages, work-life expectancy, and wages lost before the return to the labor market.72

A rehabilitation expert determines the plaintiff’s wage earning capacity—both before and after the accident—by analyzing the plaintiff’s work history and career goals.73 The post-accident earning capacity is relatively easy to determine: the rehabilitation expert evaluates the skills of the plaintiff and identifies the highest paying jobs in which the plaintiff could function effectively.74 It is more difficult, however, to determine the plaintiff’s pre-accident earning capacity.75 Where the plaintiff has an established work identity, such as remain[*PG439]ing in the same job for twenty years, the rehabilitation expert must consider the plaintiff’s actual earnings as well as “the ability of that individual to receive, hold or absorb additional skills of a vocational nature which would in effect increase his potential to earn.”76

Where the plaintiff does not have an established and consistent work identity, the rehabilitation expert must evaluate the plaintiff’s expressed and implied career goals, as well as the likelihood that the plaintiff would actually achieve those goals.77 Some courts have attempted to narrow this prediction: in one wrongful death action, for instance, the Illinois Court of Appeals held that evidence of the plaintiff’s career goals was inadmissible unless the plaintiff could show that those goals would have been “reasonably certain” to occur.78 The issue on appeal was whether the trial court had erred in admitting testimony from the decedent’s colleague that, had the decedent lived, he would have become dean of Southern Illinois University.79 The Court of Appeals found that because “becoming dean of the University was not merely an ‘ambition’ of decedent’s, but rather a goal which decedent had the ability to attain,” it was reasonably certain to occur and therefore the testimony was admissible.80

Even with legal limits on the breadth of these predictions, they remain speculative. The rehabilitation expert must evaluate the plaintiff’s skills, intelligence, and adaptability, and translate this hard data into a vocational category based primarily on “relevant” statistics about the career paths of similarly situated people.81 Because this translation becomes the major determinant of the damages for plaintiffs with little or no earnings record, it is imperative that the rehabilitation expert select a vocational category that reflects the plaintiff’s “maximum capacity for developing vocational potential and earning potential both pre and post accident.”82 If the rehabilitation expert predicts a low-paying vocation, the plaintiff’s earning capacity will be correspondingly low, but if the rehabilitation expert makes optimistic predictions, the plaintiff’s chances improve for a higher damage award.83

[*PG440] After the rehabilitation expert has identified the plaintiff’s pre-earning and post-earning capacity in terms of vocational categories, it falls to the economist to assign a value to the gathered data and compare the pre-accident earning capacity to the post-accident earning capacity.84 The economist must consult a variety of statistics to determine worker productivity, appropriate growth trends, work-life expectancy, and average earnings for workers in the vocations identified by the rehabilitation expert.85 At least until recently, courts and experts relied on statistics that were organized according to age, race, and gender.86 For example, a United States Department of Commerce table on average earnings reports that in 1987, for full-time workers between the ages of twenty and twenty-four, the mean earnings of black men were approximately 16% less than the mean earnings of white men.87 Similarly, work-life expectancy—a factor that helps calculate loss of earning capacity by predicting how long certain individuals will remain in the labor force—is also arranged by gender and race.88 Data from the 1979 to 1980 United States Bureau of Labor Statistics show that the work-life expectancy of a thirty year-old white man was 4.7 years longer than that of a minority man, 8.7 years longer than that of a white woman, and 9.2 years longer than that of a minority woman.89

C.  The Special Case of the Child-Plaintiff

Lead paint plaintiffs are ordinarily young children from poor, minority families.90 Determining loss of earning capacity for these plaintiffs is especially speculative, since child-plaintiffs lack an established record of earnings, well-developed skills, and expressed career goals.91 When confronted with a young lead paint plaintiff, experts [*PG441]often rely on a combination of objective and subjective data to predict loss of earning capacity.92 As with an adult plaintiff, objective statistics predict work-life expectancy and average wages based, to a large extent, on the child’s race.93 Subjective data focuses on the child-plaintiff’s intelligence and education, as well as the education and career paths of her parents and siblings.94 The fact-finder’s final calculation commonly involves a combination of both objective and subjective factors.95

1.  Speculation and Jury Discretion

The speculative nature of calculating lost earning potential and the amount of discretion bestowed upon the fact-finder is compounded when, as in lead paint litigation, the plaintiff is a young child.96 Ordinarily, as discussed above, the rehabilitation expert and the economist rely heavily on a pattern of earnings to establish pre-accident and post-accident earning capacity.97 Where there is no pattern of earnings, experts look to the plaintiff’s skills, intelligence, adaptability, and career goals. Child-plaintiffs lack not only an established earnings history, but also clearly defined skills and measurable career aspirations.98 As the First Circuit Court of Appeals noted, monetary damages are relatively easy to establish accurately when the plaintiff has lived “long enough to show characteristics from which his earnings may be anticipated. . . . A small child, however, presents a special problem—absent some extraordinary demonstrations, there is nothing individual to go on.”99

Child-plaintiffs, however, are not precluded from recovering for loss of earning capacity.100 To the contrary, courts have proven to be quite lenient in allowing at least some damages even where there is no [*PG442]evidence on which to base an award.101 For instance, in Murray v. Sanford, the teenage plaintiff was seriously injured in a car accident.102 Although she had no earnings history and she presented no evidence quantifying the monetary loss, the court allowed an award for loss of future earnings.103 In cases where the plaintiff is too young to have an established earnings record, the court explained, “the amount of damages awardable for permanent injury rests in the sound discretion of the jury . . . [to be exercised] in light of the jury’s own common observation and experience.”104

The Texas Court of Appeals exhibited the same liberalism in Pipgras v. Hart, where a falling brick column had severely injured a four year-old.105 Despite a complete lack of direct testimony about the impact of the injury to the child’s ability to function and his capacity to earn, the court allowed the jury to determine lost earning capacity simply from their “common knowledge and sense of justice.”106

Juries and judges are afforded broad discretion in determining damage awards for child-plaintiffs.107 However, cases like Murray and Pipgras—where the parties present no quantifying evidence of the loss of earning capacity—are rare; experts generally present extensive interpretations of statistical and personal data to make their predictions less speculative.108 Typically, then, judges and juries base their discretionary decisions on a combination of objective and subjective data.109

2.  Objective Statistics

For child-plaintiffs who have no established earnings records, both statistical averages (objective statistics) and personal data (subjective data) are the determinants in a fact-finder’s discretionary decision.110 Objective statistics, which are the traditional method of de[*PG443]termining loss of earning capacity for adults, project future income and work-life expectancy.111 These statistics are arranged primarily around race, gender, and age.112

The economic analysis of the objective statistics for a child-plaintiff is the same as the analysis for an adult.113 In both instances, the economist consults gender, age, and race-based tables to predict the number of years that the plaintiff would have remained in the labor force and to determine his or her expected average wages.114 With a child, however, the prediction is especially speculative because the averages could change drastically over an entire lifetime. Although judges and juries are afforded a large degree of discretion regarding child-plaintiffs, the ultimate damage award tends to bear a close relation to the objective predictions.115

In Drayton, for instance, the Sixth Circuit Court of Appeals overruled the District Court’s damage award, noting that the trial judge had gotten emotionally involved in the outcome of the case and thus accepted the “astronomical projections and assumptions made by plaintiffs’ expert. . . .”116 The plaintiff was a seven year-old African-American girl who had been severely disfigured from a liquid drain cleaner chemical burn.117 Her economist ignored her age, race, and gender in his calculations of loss of future income, relying instead on the average income standards for male college graduates.118 In response, the Sixth Circuit emphasized that despite the broad discre[*PG444]tion, the fact-finder must “keep such extrapolations within reasonable bounds and insure that they conform to the evidence.”119

Until recently, the use of race-based tables and statistics went virtually unchallenged.120 In O’Connor v. United States, a wrongful death suit, the Second Circuit Court of Appeals rejected the trial judge’s decision to use a statistic which measured the mortality of the “general populace.”121 Instead, the Second Circuit held that the calculation should be based on a race-specific statistic—that is, a figure that measured the life expectancy of white males only.122 The Supreme Court of Alaska maintained a similar focus on race and gender in determining the lost earning capacity of a child-plaintiff injured in a car accident.123 The only figures that the court cited related to white Alaskan females.124 In addition, in Johnson v. Misericordia Community Hospital, the Wisconsin Court of Appeals complacently accepted the usage of race-based tables.125 The court upheld the jury’s determination of the partial loss of earning capacity, noting specifically that it was based on United States Department of Commerce records arranged according to race, gender, and age.126

[*PG445]3.  Subjective Data

When appraising a child-plaintiff, the economist ordinarily does not make objective predictions for a child-plaintiff unless a rehabilitation expert has produced some subjective data.127 That is, the economist cannot calculate the plaintiff’s work-life expectancy or average earnings without some indication as to what type of career path the child would have followed had the accident not occurred.128 Subjective data reflect an examination of the particular plaintiff and the members of his or her family.129

The rehabilitation expert gathers the subjective data. He or she evaluates the plaintiff on educational capacity through IQ and aptitude tests, examines the socio-economic status of the plaintiff’s family, including the education and work history of the plaintiff’s parents and siblings, and analyzes the family’s economic ability to provide higher education.130 This subjective analysis is crucial, according to one study, because the major determinants of a child’s occupation are: the father’s occupation, education, and income; the child’s IQ; the number of siblings; the stability of family life; and the birth order of the individual relative to his or her siblings.131 The basic assumption of these factors is that, but for the accident, the child-plaintiff [*PG446]would have followed in the socio-economic footsteps of those around him or her.132

In the 1947 case of Armentrout v. Virginian Railway Co., where the defendant’s train struck and injured the four year-old plaintiff, the court used subjective data to determine loss of earning capacity.133 The court found that the jury had discretion to assume that the plaintiff would have participated in some recognized trade because he was “above average in intelligence, and . . . his parents, as shown both by evidence and by their appearance and demeanor, [were] respectable and moderately well educated people, who would likely give to their children good educational opportunities.”134 More recently, in Athridge v. Iglesias, a fifteen year-old plaintiff suffered numerous physical injuries and permanent brain damage as a result of a car accident with the defendant.135 To determine the loss of the plaintiff’s earning capacity, the court looked at a number of factors, including the likelihood that he would graduate from high school, college, or graduate school (based on information from the plaintiff’s college-prep high school), the education of his parents and siblings, and his expressed interest in becoming a lawyer.136

Thus, where the plaintiff is a child, the fact-finder frequently ascertains the damage award from a combination of objective and subjective data.137 The Drayton court emphasized the importance of the objective statistics (based on race, age, and gender) in determining damages for a child-plaintiff.138 The Armentrout and Athridge courts relied heavily on subjective information to make their discretionary decision—examining not only the plaintiff but also her family, their socio-economic status, and their education levels.139 For lead paint [*PG447]plaintiffs, however, this method of calculating damages is detrimental and results in inferior damage awards.140

III.  Identifying the Problem: Damage Determinations Are Discriminatory for Lead Paint Plaintiffs

For lead paint plaintiffs, reliance on objective and subjective data is harmful.141 Lead paint plaintiffs are almost always young children who lack past earnings, vocational experience, well-developed skills, and expressed career aspirations.142 Consequently, experts predicting loss of earning capacity for lead paint plaintiffs adhere closely to the statistics and personal data.143 But these plaintiffs also tend to be members of minorities—and the objective and subjective data that is so crucial for child-plaintiffs discriminates against minority plaintiffs.144 Lead paint plaintiffs are seriously disadvantaged by this damage award system.145

A.  Problems with Objective Statistics

Experts and courts who rely on objective statistics reason that, despite modern efforts to eradicate disadvantages for minorities, race does reflect how these groups fare in the workforce.146 However, these statistics have two significant problems. First, they reinforce the status quo of racial disparities, ignoring both the upward mobility of the individual and the upward mobility of certain groups in society.147 Second, organizing the statistics around race propels race to the forefront of predictions about individual achievement and fails to recognize that many other factors influence an individual’s ability to fulfill his or her potential.148

As Professor Chamallas has pointed out, the “traditional acceptance of the use of race-based . . . economic data creates a pattern of [*PG448]awards that replicates the status quo by reinforcing the race privilege of whites.”149 Relying upon the objective statistics recognizes that minorities, on average, make less money than white people and assumes that this discrepancy will continue.150 The statistics embody inherent stereotypes and historical discrimination. Tables of average earnings, for instance, reflect traditional wage discrimination and vocational segregation.151 Similarly, tables of work-life expectancy reflect the traditional displacement of minorities into irregular employment with few opportunities for upward mobility, as well as higher risks of incarceration for minority men.152 As long as the statistics are organized along racial lines, the ensuing damage awards for lead paint plaintiffs “assume that the current . . . racial pay gap will continue in the future, despite ongoing legal and institutional efforts to make the workplace more diverse and less discriminatory.”153 Calculations based on these statistics exclude the possibility that an individual or a group could make great advances over a lifetime.154

Race-based statistics exclude consideration of religion, ethnicity, or marital status.155 Moreover, the racial focus suggests that race has a greater impact on the achievements of a person than other factors correlated with success, such as a good-natured personality, a strong adult role model during childhood, and well-developed social skills.156 It is this concentration on race that allows devaluation to negatively affect lead paint plaintiffs.157 That is, the

willingness to believe that race . . . [is a] reliable indicator of future earning capacity relates to causal attribution. . . . [T]he use of race to predict future earnings signals a willingness to ascribe the low incomes of African-Americans to internal factors, such as lack of motivation, lack of initiative, and lack of intelligence. Such a focus on dispositional factors [*PG449]can conveniently explain why the racial income gap will persist in the future, in spite of the formal legal commitment to equal opportunity. If this is the case, then negative stereotypes can become self-fulfilling prophecies as predictions about future potential translate into lower damage awards.158

Indeed, lead paint plaintiffs are seriously injured by this devaluation—their youth induces speculative reliance on the objective statistics, and the color of their skin induces the fact-finder to accept (perhaps unconsciously) stereotypes and historical discrimination.159

B.  Problems with Subjective Data

Reliance on the subjective data assumes that child-plaintiffs are restricted by the socio-economic, educational, and vocational status of their families.160 For instance, to predict what level of educational achievement an injured child would have attained if the accident had not happened, experts often focus on the educational level of the parents and siblings.161 A lead paint plaintiff is doubly constrained by subjective data. As a child, she is constrained by the possible shortcomings of her family; as a member of a minority, she is constrained by historical racial discrimination.162 Indeed, “because of the high correlation between minority race and lower socio-economic status, assessment of the future educational attainment of minority children [and therefore the predictions of their earning capacity] will likely be negatively affected by the socio-economic situation of their families.”163

The disadvantages of subjective data are also illustrated in the discovery phase of lead paint litigation cases.164 Traditional tort cases focus on the individual, assuming that a personal injury plaintiff has willingly put her physical and even mental fitness in the spotlight for discovery.165 According to Professor Jennifer Wriggins, however, lead paint cases have seen a shift from plaintiff-centered discovery to dis[*PG450]covery regarding the plaintiff’s family.166 Lead paint defendants routinely ask for production of medical, psychological, educational, and employment records for relatives and non-parties in order to prove that the child’s injuries were caused by genetic deficiencies or poor parenting rather than by lead poisoning.167

In both the discovery context and the damages analysis,168 this shifting focus from the individual to the family is discriminatory against poor and minority families.169 This new focus on the plaintiff’s social environment “takes place against a powerful historical backdrop . . . of racist, sexist, anti-Semitic, classist intelligence research.”170 This subjective data relies on the assumption that an individual’s achievement is limited by her genetic inheritance.171 Historically, “scientific” studies of genetic inheritance were driven by the belief that African-Americans were genetically intellectually inferior and thus passed their inferiority down to their children.172 This restrictive vision of minority children correlates with lower damage awards: because these children could not have overcome the genes they inherited from their parents, the argument goes, their capacity to earn is constrained by their race and their parentage.173

IV.  Proposals for Changing Traditional Discriminatory Determination of Lead Paint Damages

The problems with both objective and subjective data should not be ignored. This Note advocates two proposals for addressing the discriminatory effects of using this data to determine lead paint damages. First, courts should substitute race-neutral statistics to calculate [*PG451]loss of earning capacity for lead paint plaintiffs—following the lead of pioneer courts such as the District of Columbia District Court and the Supreme Court of Virginia.174 In addition, courts should begin to examine the psychological theory of “resiliency,” which examines children who flourish despite adverse conditions of poverty or racial discrimination.175 This theory suggests factors other than race contribute to achievement. Making use of these factors in calculating loss of earning capacity could mitigate current racial discrepancies.176

A.  Using Race-Neutral Statistics to Determine Damages

Objective data reinforces the status quo and assumes that race is the primary determinant in measuring who and what a child-plaintiff would have become.177 To combat the discrimination for young minority plaintiffs, commentators and lawyers have suggested that courts reject the race-based statistics and opt instead for race-neutral statistics.178 As scholar Sherri Lamb asserts, “the most desirable nondiscriminatory option is to consider each person as equivalent to the average, unless evidence is produced which removes the plaintiff from the normal range.”179

Within the past ten years, some courts have rejected race-based statistics to measure loss of earning capacity.180 In 1990, for example, the Virginia Supreme Court held that statistics organized solely around race, age, and sex were insufficient to calculate loss of earning capacity.181 The plaintiffs in that case had sued their obstetrician-gynecologist to recover for birth defects caused by the failure to pro[*PG452]vide medical care during labor and delivery.182 Ruling that the plaintiffs had not proved damages with “reasonable certainty,” the court commented that “such evidence [of loss of earning capacity] must relate to facts and circumstances personal to the plaintiff as an individual, not merely to his membership in a statistical class.”183 In other words, the court required more than averages based (in large part) on race; on their own, such statistics were too speculative to have accurate predictive value.184

Then, in the 1991 Wheeler case, the District of Columbia District Court adopted race-neutral statistics in favor of race-based statistics to determine loss of earning capacity.185 The plaintiff was an overseas employee of the United States at the time of the injury who sued the State Department for failure to provide appropriate medical care to her son.186 The defendants appealed the lower court damage award, arguing that the award should be reduced to conform to race-based statistics.187 The court, however, held that “it would be inappropriate to incorporate current discrimination resulting in wage differences between the . . . races or the potential for any future such discrimination into a calculation for damages resulting from lost wages.”188 Instead, the court employed a measurement of average earnings of all American college graduates without regard to race.189 The court con[*PG453]cluded that using race-neutral data was the best method of maintaining accuracy while eliminating discrimination.190

Interestingly, the Wheeler court’s decision to forego the use of data based on either race or gender resulted in a damage award for the plaintiff that was even lower than the defendant had suggested.191 That is, the average wages for all persons turned out to be lower than the average black male wages.192 The court made a corresponding award for this plaintiff.193

Widespread adoption of race-neutral statistics for lead paint plaintiffs could help mitigate the current racial discrimination in damage awards.194 Rejecting race as a determinant will help courts break free from the status quo of discrimination within the work-force.195 In theory, using race-neutral statistics allows for the possibility that the current racial discrepancies will be relieved.196 In practice, however, when courts use statistics which are both race- and gender-neutral, they might actually reduce damage awards for all plaintiffs, as in the Wheeler case.197 But decreasing the focus on race does, at least, encourage courts to look to other factors to predict an individual’s potential.198 The psychological theory of resiliency suggests factors beyond race that impact a child’s potential.199 These factors may work to overcome the practical effects of using race-neutral statistics by increasing the recovery for lead paint plaintiffs.200

B.  Introducing Resiliency Theory into Damage Determinations

Adopting race-neutral statistics is only one of the ways in which courts can mitigate the disappointing and discriminatory damages for lead for lead paint plaintiffs. A second proposal comes from the psychological/developmental theory of resiliency.201 Resiliency theory is [*PG454]useful on three levels. First, it identifies concrete factors—other than race—that indicate a likelihood of success despite adverse conditions.202 Second, the multitude of resiliency literature confirms that predictions about what a child is likely to become are enormously speculative.203 And third, resiliency theory provides a theoretical alternative to the devaluation of racial minorities by starting with the optimistic assumption that children are very much capable of succeeding beyond the averages and against the odds.204

Traditionally, child psychology and development research has focused on why children fail.205 This pessimism is the same pessimism that infiltrates the measurement of damages in lead paint cases: it is grounded in a basic assumption that children in adverse situations will be constrained by those situations and will fall victim to adversity.206 Resiliency theory, on the other hand, is unique because it starts from the proposition and expectation that “there are kids in families from very adverse situations who really do beautifully, and seem to rise to the top of their potential, even with everything else working against them.”207

In its simplest and least technical form, the study of resilience examines how people respond to stress and adversity.208 In other words, a resilient child is one who has delayed or defended against the developmental problems that were expected and predicted in light of the child’s biological or psychological status, or the child’s [*PG455]surrounding environment.209 As one scholar noted, “[r]esilience is a quintessentially U.S. concept. It has roots in the U.S. hero myth commemorated in [“rags-to-riches”] books and stories by Horatio Alger. . . .”210

Despite methodological variances,211 resiliency studies identify certain “risk” factors, which create adverse conditions for children, and “protective” factors, which help children cope with stress.212 “A risk factor is an individual attribute, individual characteristic, situational condition, or environmental context that increases the probability” of an undesirable outcome.213 Extreme poverty is one of the most widely identified risk factors.214 Protective factors, which can neutralize and sometimes overcome the risk factors, include both individual characteristics215 as well as environmental characteristics: intelligence, social skills, easy disposition, good-natured personality, strong attachment to parents, and association with a good school and other pro-social institutions.216

In 1982, social psychologists Emmy E. Werner and Ruth S. Smith published a study of 698 people on the Hawaiian island of Kauai.217 One third of those surveyed had been born into families affected by [*PG456]poverty, divorce, alcoholism, mental illness, and physical abuse.218 Despite these conditions, however, 25% of this subset matured to lead stable, satisfying lives.219 The authors of the study found that certain characteristics allowed these individuals to overcome the risks that confronted them from birth:

the age of the opposite-sex parent (younger mothers for resilient males, older fathers for resilient females); the number of children in the family (four or fewer); the spacing between the index child and the next-born sibling (more than [two] years); . . . the amount of attention given to the child by the primary caretaker(s) in infancy; . . . the presence of an informal multigenerational network of kin and friends in adolescence; and [a low] cumulative number of chronic stressful life events experienced in childhood and adolescence.220

At the core of resiliency theory is the realization that children living under extreme conditions (such as poverty) can rise far beyond what is expected of them.221

For lead paint plaintiffs, this notion can have a significant impact. Practically speaking, resiliency theory argues against full reliance on the objective and subjective data.222 In identifying specific protective factors, resiliency theory encourages experts to broaden the sources for their predictions of future earning capacity, no longer relying on race and gender as the sole determinants.223 Although it remains to be seen how exactly an expert could measure the protective factor and its precise impact, resiliency theory offers the possibility of mitigating the current overwhelming discrimination against lead paint plaintiffs.224

Using resiliency theory to determine loss of earning capacity also has two theoretical consequences. First, a review of the resiliency literature confirms that loss of earning capacity is a speculative and inexact prediction.225 Psychologists have spent enormous amounts of [*PG457]time and energy trying to discern exactly how children manage to function well when confronted with poverty or racial discrimination.226 Courts have consistently recognized the speculative nature of predictions of what a child would have become.227 Although experts have tried to ground their predictions in subjective and objective data,228 resiliency theory suggests that courts should be open to other sources of data in calculating damage awards.229

Finally, resiliency theory challenges the often fatalistic vision that economists and rehabilitation experts develop in relation to at-risk children.230 Statistical averages and examinations of the plaintiff’s family assume that the child will not succeed beyond the predicted averages for education, socio-economic status, and vocational opportunities.231 Resiliency theory, on the other hand, begins with the assumption that children do succeed.232 As psychologist Ann Matsen explains, although “extreme adversity can have devastating effects on development . . . our species has an enormous capacity for recovery.”233 Recognizing and rewarding lead paint plaintiffs for their capacity to recover, rather than punishing them with low damage awards based on the color of their skin, is a simple step towards eradicating racial discrimination in the tort system and in the legal system.


Lead poisoned children have been inadequately compensated for their injuries. Their age—and the absence of any earnings history or defined career path—encourages courts to rely heavily on statistics and to judge the children within the context of the achievements of their family members. For children from low-income and minority families, however, this reliance reinforces historical discrimination and results in damage awards that reflect subtle but pervasive racism and classism.

[*PG458] There is no magic formula to calculate a child’s worth. Tort law requires a mathematical figure in order to compensate the victim. Consequently, courts should begin with the assumption that every child has the potential to surpass the conservative predictions of an economist or a rehabilitation expert. To implement this assumption, courts must expand the focus of damage awards for lead paint plaintiffs beyond race and socio-economic status. Adopting race-neutral statistics and integrating resiliency theory into damage awards are steps towards a less discriminatory theory of compensation and a more optimistic and accurate determination of a child’s potential.

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