* Articles Editor, Boston College Environmental Affairs Law Review, 2000–01.
1 See United States Environmental Protection Agency, Lead and Lead Poisoning (visited Jan. 23, 2000) <http://www.epa.gov/r02earth/health/leadpoisoning.htm> [hereinafter EPA, Lead and Lead Poisoning].
2 See Martha Mahoney, Four Million Children at Risk: Lead Paint Poisoning Victims and the Law, 9 Stan. Envtl. L.J. 46, 51 (1990); United States Department of Human Services, Public Health Service, Agency for Toxic Substance and Disease Registry, Case Studies in Environmental Medicine: Lead Toxicity (visited Jan. 15, 2000) <http://wonder.cdc.gov/ wonder.prevguid/p0000017/entire.htm> [hereinafter USDHHS, Case Studies].
3 See, e.g., Valencia ex rel Franco v. Lee, 123 F. Supp. 2d 666 (E.D.N.Y. 2000); Hiraldo v. Kahn, 267 A.D.2d 205 (N.Y.S. 2d 1999); Parker v. D’Avolio, 664 N.E.2d 858, 864 (Mass. App. Ct. 1996) (upholding judgment in favor of child in action against landlord for lead paint poisoning).
4 See Martha Chamallas, Questioning the Use of Race-Specific and Gender-Specific Economic Data in Tort Litigation: A Constitutional Argument, 63 Fordham L. Rev. 73, 75 (1994)[hereinafter Chamallas, Questioning].
5 See Athridge v. Iglesias, 950 F. Supp. 1187, 1192–93 (D.D.C. 1996); Armentrout v. Virginian Railway Co., 72 F. Supp. 997, 1001 (S.D. W. Va. 1947); Bulala v. Boyd, 389 S.E.2d 670, 677–78 (Va. 1990).
6 See generally Mahoney, supra note 2, at 49; Martha Chamallas, The Architecture of Bias: Deep Structures in Tort Law, 146 U. Pa. L. Rev. 463 (1998)[hereinafter Chamallas, Architecture of Bias]; Jennifer Wriggins, Genetics, IQ, Determinism, and Torts: The Example Of Discovery In Lead Exposure Litigation, 77 B.U. L. Rev. 1025 (1997).
7 See Chamallas, Questioning, supra note 4, at 97.
8 See Chamallas, Architecture of Bias, supra note 6, at 483.
9 See Wriggins, supra note 6, at 1028–31.
10 As Professor Martha Chamallas explains, “the past is uncritically accepted as a guide to the future, even though most people acknowledge that the past was hardly free of race . . . bias.” Chamallas, Architecture of Bias, supra note 6, at 488–89.
11 See, e.g., Wheeler Tarpeh-Doe v. United States, 771 F. Supp. 427, 455 (D.D.C. 1991), rev’d on other grounds, Tarpeh-Doe v. United States, 28 F.3d 120 (D.C. Cir. 1994); see also infra section IV(A).
12 See generally Resilience and Development: Positive Life Adaptations 17 (Meyer D. Glantz and Jeannette L. Johnson eds., 1999).
13 Meyer D. Glantz & Zili Sloboda, Analysis and Reconceptualization of Resilience, in Resilience and Development, supra note 12, at 109, 114–115.
14 See id.
15 See E. James Anthony, Risk, Vulnerability, and Resilience: An Overview, in The Invulnerable Child, 3, 10–11 (E. James Anthony & Bertram J. Choler eds., 1987) (due to the enormous diversity of risks to which children are exposed, predictions of the “outcome” are extraordinarily complex).
16 See Chamallas, Architecture of Bias, supra note 6, at 487. See generally David Gelman, The Miracle of Resiliency, Newsweek, May 1991, at 44.
17 See United States Environmental Protection Agency, LEAD: General Information and Region 3 Highlights (visited Jan. 23, 2000) <http://www.epa.gov/reg3artd/indoor/lead. htm> [hereinafter EPA, LEAD].
18 See Theodore I. Lidsky and Jay S. Schneider, Evaluating the Poisoned Mind, 36 Trial 32 (2000).
19 See id.
20 See EPA, Lead and Lead Poisoning, supra note 1.
21 See USDHHS, Case Studies, supra note 2.
22 See Lidsky, supra note 18. It is possible that the CDC will adjust this estimate in the future as it has done in the past, lowering the figure to keep up with technological and medical developments. See Mahoney, supra note 2, at 51–52.
23 See Lidsky, supra note 18, at 34 n.3; EPA, LEAD, supra note 17.
24 See USDHHS, Case Studies, supra note 2 (“[t]he amount of lead absorbed from the [gastrointestinal] tract of adults is typically 10% to 15% of the ingested quantity; for pregnant women and children, the amount absorbed can increase to as much as 50%.”).
25 See Lidsky, supra note 18, at 32, 34 n.3.
26 See USDHHS, Case Studies, supra note 2.
27 See Donald E. Lively, The Diminishing Relevance of Rights: Racial Disparities in the Distribution of Lead Exposure Risks, 21 B.C. Envtl. Aff. L. Rev. 309, 315 (1994).
28 See United States Department of Health and Human Services, 1997 News Release: Blood Lead Levels Keep Dropping; New Guidelines Proposed for Those Most Vulnerable (visited Feb. 15, 2000) <http://www.cdc.gov/nchs/releases/97news/97news/bldlead.htm> [hereinafter USDHHS, 1997 News Release].
29 See Lively, supra note 27, at 316; Center for Disease Control and Prevention, What Every Parent Should Know About Lead Poisoning in Children (visited Jan. 23, 2000) <http:// www.cdc.gov/nceh/programs/lead/faq/cdc97a.htm>.
30 Lively, supra note 27, at 316.
31 USDHHS, Case Studies, supra note 2 (African-American and other minority groups are over-represented in low-income groups as well as in the inner-cities).
32 See Lively, supra note 27, at 316. Professor Lively emphasizes the impact of the “white flight” phenomenon on racial segregation and increased exposure risk for minorities within the past three or four decades: “white flight denotes the process of population redistribution in which whites leave a community, usually an older city, and settle in suburbs[,]” thereby creating “newer and predominantly white suburbs and older and largely black inner cities . . .” and creating the concentration of minority families in urban areas with high exposure risks. See id. at 316 n.64, 317.
33 See EPA, Lead and Lead Poisoning, supra note 1. Although children with lead poisoning span all socio-economic and racial divisions, the “prevalence of elevated levels, nevertheless, remain highest among inner-city, underprivileged children[.]” See USDHHS, Case Studies, supra note 2; see also Lively, supra note 27, at 316–17.
34 See, e.g., Center for Disease Control, Morbidity and Mortality Weekly Report, Childhood Lead Poisoning, New York City, 1988 (visited Feb. 15, 2000) <http://www.cdc.gov/epo/ mmwr/preview/mmwrhtml/00001890.htm>.
35 See id. Unfortunately for analysis purposes, these statistics vary widely: the CDC estimated that in 1984, African-American children accounted for 46% of the children at risk. See USDHHS, Case Studies, supra note 2.
36 See Lively, supra note 27, at 317 (citing Agency for Toxic Substances and Disease Registry, The Nature and Extent of Lead Poisoning in the United States: A Report to Congress (1988) [hereinafter ATSDR]) (referring to families with annual income under $6000).
37 See id.
38 See USDHHS, 1997 News Release, supra note 29. The CDC press release cites to the findings of a National Health and Nutrition Examination Survey. See id.
39 See USDHHS, Case Studies, supra note 2.
40 See id.; Lively, supra note 27, at 315 (noting that old water pipes and soil near streets and highways pose contamination risks, but stating that primary source of lead poisoning is lead-based paint).
41 See supra notes 29–33 and accompanying text.
42 USDHHS, Case Studies, supra note 2.
43 See id.
44 See id.
45 See id. Lead poisoning can damage the endocrine system as well, interfering with the metabolism of Vitamin D and calcium, and affecting cell maturation and skeletal growth. See id.
46 See Mahoney, supra note 2, at 50.
47 See USDHHS, Case Studies, supra note 2.
48 See infra note 54 and accompanying text.
49 See generally Chamallas, Architecture of Bias, supra note 6; Chamallas, Questioning, supra note 4.
50 See generally 8 Paul M. Deutsch & Frederick A. Raffa, Damages in Tort Actions �� 108–110 (1982).
51 See infra note 3.
52 See Harry L. Miles, Damages for Personal Injury, in Damages in Massachusetts Litigation, � 8, � 8–16 (1993).
53 See Parker & Waichman, Lead Poisoning and Its Effects on Children (visited Jan. 23, 2000) http://usalawinfo.com/lead/cfm. One estimate reported that there were over 1500 lead-related cases in Boston and Baltimore alone in 1993. See id. (also reporting cities all over the country encountering comparable increases); see also Wriggins, supra note 6, at 1026–28 (despite federal laws regulating use of lead paint, plaintiffs have instituted a “substantial” number of tort cases against landlords).
54 See Michael A. Pope, Novel Damage Theories in Toxic Tort Litigation, 497 PLI/Lit 167, 169 (1994).
55 See Mark F. Itzkowitz, Lead Poisoning Liability, in Massachusetts Premises Liability � 5, � 5.10 (1997). Under Massachusetts law, for instance, a property owner might be liable for punitive damages of three times the amount of actual damages for failure to comply with lead paint regulations. See Mass. Gen. Laws ch. 111, � 199(b) (1994).
56 Battista v. U.S., 889 F. Supp. 716, 724 (S.D.N.Y. 1995).
57 See Chamallas, Architecture of Bias, supra note 6, at 464 (“[m]ost empirical studies indicate that women of all races and minority men continue to receive significantly lower damage awards than white men in personal injury . . . suits”); see also Chamallas, Questioning, supra note 4, at 84–85.
58 See generally Audrey Chin & Mark A. Peterson, Deep Pockets, Empty Pockets: Who Wins in Cook County Jury Trials (1985); Frank M. McClellan, The Dark Side of Tort Reform: Searching for Racial Justice, 48 Rutgers L. Rev. 761 (1996).
59 See McClellan, supra note 59, at 774.
60 See id.
61 See Chamallas, Architecture of Bias, supra note 6, at 480.
62 See id. at 467; infra section II(B)(2).
63 See id.
64 See Chamallas, Architecture of Bias, supra note 6, at 480.
65 Id.
66 136 A.2d 918, 924 (Conn. 1957); Chamallas, Questioning, supra note 4, at 75.
67 Chamallas, Architecture of Bias, supra note 6, at 480.
68 See Deutsch & Raffa, supra note 50, �� 109.00–.01; see also Anderson v. Litzenberg, 694 A.2d 150, 161 (Md. Ct. Spec. App. 1997) (award of damages for impairment of earning capacity seeks to compensate plaintiff for reduction in ability to earn through personal services). When measuring loss of earning capacity, a court must determine the value of the plaintiff’s “capacity to earn money by [her] labor, physical or intellectual. . . . [T]he [c]ourt is only indirectly concerned with whether the [plaintiff] would in fact have utilized her earning power at any given time so as to produce actual income.” Feldman v. Allegheny Airlines, Inc., 382 F. Supp. 1271, 1282 (D. Conn. 1974), aff’d in part, rev’d in part, 524 F.2d 384 (2d Cir. 1975).
69 Deutsch & Raffa, supra note 50, � 108.00, at 108–2.
70 See Meshell v. Lovell, 732 So.2d 83, 87 (La. Ct. App. 1999), writ denied, 744 So.2d 626 (La. 1999); Wal-Mart Stores, Inc. v. Ard, 991 S.W.2d 518, 522–23 (Tex. App. 1999).
71 See Petrus v. Bain, 742 So.2d 739, 744–45 (La. Ct. App. 1999); Meshell, 732 So.2d at 87 (“[a]n award for loss of earning capacity is inherently speculative and not always calculable with mathematical certainty”); Wal-Mart, 991 S.W.2d at 522–26 (court unwilling to find jury’s damage award excessive since evidence was sufficient and jury can rely on own sound judgment); Pipgras v. Hart, 832 S.W.2d 360, 365 (Tex. App. 1992); Tri-State Motor Transit Co. v. Nicar, 765 S.W.2d 486, 492 (Tex. App. 1989) (examining particular facts of each case to determine loss of earning capacity because loss of future earning capacity “is always uncertain and is left largely to the jury’s sound judgment and discretion”); see also Questioning, supra note 4, at 84 (although experts can provide foundation for damage award determinations, juries are not restricted to expert evidence when calculating loss of future earning capacity).
72 See Deutsch & Raffa, supra note 50, � 109.80, at 109–27. According to Professor Chamallas, the most significant factors in the determination of loss of earning potential are the plaintiff’s work-life expectancy and the prediction of the plaintiff’s average wages. See Chamallas, Architecture of Bias, supra note 6, at 481; see also Larry R. Rogers & Kelly N. Warnick, Impaired Earning Capacity: Plaintiff’s Perspective in Proving and Disproving Damages in Personal Injury Cases, in P & DD IL-CLE, � 5.2 (1993) (factors include plaintiff’s chosen livelihood, plaintiff’s alternative employment paths, any efforts plaintiff could make to improve her condition or lessen detrimental effects that the injury has on ability to pursue desired career).
73 See generally Deutsch & Raffa, supra note 50, � 109.
74 See generally id. �� 109.10–.80.
75 See generally id. � 110.
76 See id. � 109.01 at 109–2.
77 See id. � 109.10 at 109–5.
78 See Lorenz v. Air Illinois, Inc., 522 N.E.2d 1352, 1355 (Ill. App. Ct. 1988).
79 See id.
80 See id.
81 See Deutsch & Raffa, supra note 50, � 109.10 at 109–5, 109–6.
82 See id.
83 See id.
84 See id. � 110.02 at 110–4 (economist’s role is “to quantify the impact of the injury in question on the future remaining lifetime earning capacity of the plaintiff”).
85 An in-depth analysis of the economics of determining loss of earning capacity is beyond the scope of this Note. For background information and a suggestion of useful statistical data, see generally id. �� 109, 110.
86 See Chamallas, Questioning, supra note 4, at 75. Where the plaintiff has a clearly established earnings history, economists do not rely on race- and gender-based statistics to determine earnings; for other calculations, however, such as work-life expectancy, the categorized statistics are deemed crucial. See id. at 80.
87 See Deutsch & Raffa, supra note 50, � 110.11[2] at 110–10.1 to 110–10.2.
88 See Chamallas, Architecture of Bias, supra note 6, at 481.
89 See id.
90 See supra, section I(A).
91 See, e.g., D’Ambra v. United States, 481 F.2d 14, 18 (1st Cir. 1973).
92 See Bulala v. Boyd, 389 S.E.2d 670, 677–78 (Va. 1990). The terms “objective” and “subjective” are not terms of art or law; rather, I have assigned them based on the types of data that they represent.
93 See supra section II(C)[2].
94 See, e.g., Athridge v. Iglesias, 950 F. Supp. 1187, 1192–93 (D.D.C. 1996); Armentrout v. Virginian Railway Co., 72 F. Supp. 997, 1001 (S.D. W. Va. 1947).
95 See id.; see also Bulala, 389 S.E.2d at 677–78 (noting need for “facts and circumstances personal to the plaintiff as an individual” because damage estimates calculated solely from statistics are too remote and speculative).
96 See Deutsch & Raffa, supra note 50, � 110.11[2], at 110–8.
97 See supra text accompanying notes 78–90.
98 See D’Ambra, 481 F.2d at 18.
99 Id.
100 See, e.g., Murray v. Sanford, 487 S.E.2d 135, 136 (Ga. Ct. App. 1997).
101 See id.
102 See id.
103 See id. at 136–37.
104 Id. at 136; see also Rubio v. Davis, 500 S.E.2d 367, 371 (Ga. Ct. App. 1998) (where no earnings history, jury must exercise discretion based on own observation and experience); C.T.W. v. B.C.G., 809 S.W.2d 788, 794 (Tex. App. 1991); Tri-State Motor Transit Co. v. Nicar, 765 S.W.2d 486, 493–94 (Tex. App. 1989).
105 See 832 S.W.2d 360, 363 (Tex. App. 1992).
106 Id. at 366.
107 See, e.g., Murray, 487 S.E.2d at 136; Pipgras, 832 S.W.2d at 366.
108 See id.; Chamallas, Questioning, supra note 4, at 82–84.
109 See, e.g., Bulala v. Boyd, 389 S.E.2d 670, 677–78 (Va. 1990).
110 See id.; see also Chamallas, Questioning, supra note 4, at 82–83(despite theoretical underpinnings for loss of future earning capacity, experts rely on race-based statistics when plaintiff has limited or non-existent earnings record); Deutsch & Raffa, supra note 50, � 110.11[2], at 110–8. Deutsch and Raffa point out that the economist is confronted with two methods of establishing the earning capacity of a child-plaintiff. See Deutsch & Raffa, supra note 50, � 110.11[2], at 110–8. On the one hand, the economist could rely on data from the United States Department of Commerce to “establish average educational levels by the sex and race of the plaintiff.” See id. Having established an education level, the economist then turns towards other data from the Department of Commerce to determine a base annual earning capacity. See id. � 110.11[2], at 110–8 to 110–9. On the other hand, there are many cases where the economist relies on subjective data in order to calculate loss of earning capacity. See id. This Note is concerned with the cases in the latter category.
111 See supra section II(B)(2).
112 See Chamallas, Architecture of Bias, supra note 6, at 483.
113 See, e.g., Drayton v. Jiffee Chem. Corp., 591 F.2d 352, 361–64 (6th Cir. 1978).
114 See Deutsch & Raffa, supra note 50, � 110.11[2], at 110–6 to 110–9; Sherri Lamb, Toward Gender-Neutral Data for Adjudicating Lost Future Earning Damages: An Evidentiary Perspective, 72 Chi.-Kent L. Rev. 299, 324 (1996).
115 See, e.g., Drayton, 591 F.2d at 362.
116 Id. at 364.
117 See id. at 355.
118 See id. at 362.
119 Id. at 362 (“no reasonable person would, in the ordinary affairs of life, act upon the astronomical projections and assumptions made by plaintiff’s expert and accepted by the District Court.”).
120 See Chamallas, Questioning, supra note 4, at 96; see also Lamb, supra note 114, at 316–18.
121 See 269 F.2d 578, 584 (2d Cir. 1959).
122 See id.; see also Powell v. Parker, 303 S.E.2d 225, 228 (N.C. Ct. App. 1983), review denied by 307 S.E.2d 166 (N.C. 1983) (not questioning the use of race to project future net income).
123 See Morrison v. Alaska, 516 P.2d 402, 404–05 (Alaska 1973).
124 See id.
125 See 294 N.W.2d 501, 527 (Wis. Ct. App. 1980), aff’d, 301 N.W.2d 156 (Wis. 1981).
126 See id.; see also Chamallas, Questioning, supra note 4, at 95–97 & 140 n.155 (noting that scholars, too, rely on race as a primary determinant in measuring loss of earning capacity for child-plaintiffs). Until recently, courts also tended to rely heavily on gender-based statistics to determine loss of earning capacity. See Lamb, supra note 115, at 316–18. Although gender-based statistics generally do not have a negative impact on lead paint plaintiffs—and therefore are somewhat outside the scope of this Note—there are a wide range of interesting cases. See Caron v. United States, 410 F. Supp. 378, 398 (D.R.I. 1976), aff’d, 548 F.2d 366 (1st Cir. 1976) (paying lip-service to the theoretical notion of equality but holding that the determination of prospective earnings must be based on “female wages” as defendant suggested, to reflect realistic inequality between sexes); Frankel v. United States, 321 F. Supp. 1331, 1333, 1337–38 (E.D. Pa. 1970), aff’d sub nom., Frankel v. Heym, 466 F.2d 1226 (3d Cir. 1972) (considering probabilities of marriage, child-bearing, child-raising, and traditionally low wages for women to determine loss of earning capacity for a female plaintiff).
127 See Deutsch & Raffa, supra note 50, � 110.11[2], at 110–8. The subjective data is important in all cases where the plaintiff does not have an established work history or earnings record. See id. � 109.01, at 109–2. Usually the plaintiff in such a situation is a child; it is possible, however, to have an adult plaintiff who lacks an earnings record or a work history, thus requiring a rehabilitation expert to synthesize relevant subjective data. See Lorenz v. Air Illinois, Inc., 522 N.E.2d 1352, 1355 (Ill. App. Ct. 1988) (rehabilitation expert evaluated plaintiff’s intelligence and adaptability to determine whether it was reasonably certain that plaintiff would have become dean of the University where he worked because plaintiff lacked work history specific to that job).
128 Deutsch & Raffa, supra note 50, �110.11[2], at 110–8.
129 See id.
130 See id. One study of the methods of analysis advises rehabilitation/vocational experts to conduct a document review, a client interview, a number of tests and evaluations, and then review and analyze the data collected. See Edmond Provder, Using Vocational Experts in Cases Involving Injured Children, 29 Trial 39, 39–40 (1993). In conducting the document review, the expert should examine medical records, educational records, and psychological records to determine the intellectual ability. See id. The client interview should be geared towards determining the extent of the injury, the level of comprehension, any remaining memory or knowledge, and the effect of the diminished ability on day-to-day activities. See id. A history of the parents and siblings should be included in the interview in order to get a baseline on occupational levels, educational levels, earnings, and psychological functioning. See id. The tests and evaluations should be “designed to measure a specific child’s education level and disabling condition.” Id.
131 Christopher J. Bruce, The Calculation of an Infant’s Lost Earnings, 22 Alberta L. Rev. 291, 292–93 (1984).
132 See Wriggins, supra note 6, at 1055–70.
133 72 F. Supp. at 999.
134 Id. at 1001.
135 Athridge, 950 F. Supp. at 1188–90, 1192.
136 Id. at 1192–93. A Canadian case also illustrates the use of the subjective analysis. See Bruce, supra note 132, at 291. The court calculated the expected loss of income for an eight year-old boy whose arm had been amputated by considering the child’s IQ, his speech and grammar problems as an infant, his inadequate performance in school since the accident, and that he was fourth in a family of seven. See id. In addition, the court noted that the father left home when the child was three and the father worked as a skilled tradesman. See id. The court concluded that, but for the accident, the child would have become an unskilled or semi-skilled laborer. See id.
137 See Drayton, 591 F.2d at 362–64; Athridge, 950 F. Supp. at 1192–93; Armentrout, 72 F. Supp. at 1001.
138 See 591 F.2d at 362–64.
139 See Athridge, 950 F. Supp. at 1192–93; Armentrout, 72 F. Supp. at 1001.
140 See generally, Chamallas, Architecture of Bias, supra note 6; Wriggins, supra note 6.
141 Id.
142 See D’Ambra v. United States, 481 F.2d 14, 18 (1st Cir. 1973); EPA, Lead and Lead Poisoning, supra note 1.
143 See, e.g., Bulala v. Boyd, 389 S.E.2d 670, 677–78 (Va. 1990); Chamallas, Questioning, supra note 4, at 820–83; Deutsch & Raffa, supra note 50, �110.11[2], at 110–8.
144 See Chamallas, Questioning, supra note 4, at 97; Wriggins, supra note 6, at 1055–70.
145 See id.
146 See Chamallas, Architecture of Bias, supra note 6, at 483. Professor Chamallas explains: “In our society . . . race . . . matter[s]: being . . . an African-American does dampen one’s earning prospects.” Id.
147 See Chamallas, Questioning, supra note 4, at 97.
148 See Glantz & Sloboda, supra note 13, at 109, 114–15.
149 Chamallas, Questioning, supra note 4, at 97.
150 See id. at 75.
151 See Chamallas, Architecture of Bias, supra note 6, at 481.
152 See id.
153 See Chamallas, Questioning, supra note 4, at 75.
154 See Chamallas, Architecture of Bias, supra note 6, at 481; Chamallas, Questioning, supra note 4, at 75, 84 (“[r]eliance on . . . race-specific data to calculate loss of future earning capacity assures that predictions about the future are tied to present disparities, disparities which are sizable and reinforce the dominant economic position of white men in the American economy.”).
155 Chamallas, Architecture of Bias, supra note 6, at 483.
156 See Glantz & Sloboda, supra note 13, at 114–15.
157 See Chamallas, Architecture of Bias, supra note 6, at 483.
158 Id. at 487.
159 See id. In fact, Professor Chamallas asserts that it is unconstitutional for a court to rely on the race-based statistics. See Chamallas, Questioning, supra note 4, at 75–76. She argues that the classifications based on race fail to further a compelling state interest. See id.
160 See Wriggins, supra note 6, at 1028–30.
161 See Chamallas, Questioning, supra note 4, at 82.
162 See id. at n.53.
163 Id.
164 See generally Wriggins, supra note 6.
165 See Wriggins, supra note 6, at 1055.
166 See id. at 1028, 1057–58. “Not surprisingly, in view of the race, gender, and class characteristics of many plaintiffs and their families, lead exposure litigation constitutes the first area in which litigants systematically seek this type of discovery.” Id. at 1088.
167 See id. at 1058–59. Many courts grant such requests from defendants: “while New Jersey and Massachusetts courts have denied defendants’ requests seeking examinations of plaintiffs’ mothers, a District of Columbia court allowed the IQ testing and psychological examination of a plaintiff’s mother and sibling, New York courts ordered IQ testing of a plaintiff’s mother in two cases, and a Louisiana court ordered the neuropsychological testing of a plaintiff’s siblings.” Id. at 1058–59.
168 Professor Wriggins predicted that this broader focus of discovery would soon extend beyond the lead paint context; certainly, at least, it has extended beyond the discovery realm and into the determination of damages. See id. at 1088.
169 See id. at 1044.
170 Wriggins, supra note 6, at 1044.
171 See id. at 1044–48.
172 See id. at 1045.
173 See id. at 1044–48; see also Bruce, supra note 132, at 291.
174 See, e.g., Wheeler Tarpeh-Doe v. United States, 771 F. Supp. 427, 455–56 (D.D.C. 1991), rev’d on other grounds, Tarpeh-Doe v. United States, 28 F.3d 120 (D.C. Cir. 1994); Bulala v. Boyd, 389 S.E.2d 670, 677–78 (Va. 1990).
175 See generally Resilience and Development, supra note 12.
176 See, e.g., Glantz & Sloboda, supra note 13, at 109, 114–15.
177 See supra section III(A).
178 See generally Chamallas, Questioning, supra note 4.
179 Lamb, supra note 115, at 338. Lamb focuses on the discrimination that stems from gender-based statistics. See id. Gender, like race, affects the calculation of work-life expectancy and average earnings. See id. at 308–15. Courts are likely to assume that a woman’s work-life expectancy will be affected by marriage, pregnancy, and raising children. See id. at 316. Also, “because the participation rate [the probability that the plaintiff will be participating in the work force] for women has been dramatically rising over the past few decades toward the male participation rate, the current tables underestimate future work life durations for women.” See id. at 310.
180 See, e.g., Wheeler, 771 F. Supp. at 454–56; Bulala, 389 S.E.2d at 677–78.
181 See Bulala, 389 S.E.2d at 677.
182 See id. at 672.
183 Id. at 678.
184 See id. The initial shift away from race-based statistics is mirrored by a minority of courts in the gender realm. See Reilly v. United States, 665 F. Supp. 976, 997 (D.R.I. 1987), aff’d in part and remanded, 863 F.2d 149 (1st Cir. 1988); Caron v. United States, 410 F. Supp. 378, 398 (D.R.I. 1976), aff’d, 548 F.2d 366 (1st Cir. 1976). Judge Pettine of the District Court of Rhode Island presents a good example of this shift. In 1976, he rejected plaintiffs’ request for a damage award based on gender-neutral data in Caron. See 410 F. Supp. at 398. Despite the court’s sympathy towards equality in employment, Judge Pettine explained, the court would base its determination on the reality of the inequality in the average earnings of the sexes. Id. But then, eleven years later, Judge Pettine changed his mind and adopted gender-neutral data. See Reilly, 665 F. Supp. at 997. He wrote:
As a factual matter, I seriously doubt the probative value of [a gender-based] statistic with respect to twenty-first century women’s employment patterns, particularly in light of current, ongoing changes in women’s labor force participation rates. . . . [In fact,] both federal and state authorities within the jurisdiction counsel against such disparate treatment.
Id.
185 See Wheeler, 771 F. Supp. at 455–56.
186 See id. at 429–30. The child-plaintiff was half-black and half-white. See id. at 455.
187 See id.
188 See id.
189 See id.
190 See Wheeler, 771 F. Supp. at 456.
191 See id. at 455–56.
192 See id. Apparently, incorporating female wages into the calculation of average wages reduced the award significantly. See id. at 456; Chamallas, Questioning, supra note 4, at 97.
193 See Wheeler, 771 F. Supp. at 455–56.
194 See id.
195 See Chamallas, Questioning, supra note 4, at 97.
196 See id. at 75.
197 See Wheeler, 771 F. Supp. at 455–56; Chamallas, Questioning, supra note 4, at 97 (noting that African-American men are disadvantaged by race-based data but tend to benefit from gender-based data).
198 See Glantz & Sloboda, supra note 13, at 114–15.
199 See id.
200 See id.
201 See generally Resilience and Development, supra note 12.
202 See Glantz & Sloboda, supra note 13, at 114–15.
203 See Anthony, supra note 15, at 10–11.
204 See generally Gelman, supra note 16.
205 See id. at 44.
206 See id.
207 Id. (quoting Dr. W. Thomas Boyce, Director of Behavioral and Developmental Pediatrics at the University of California, San Francisco).
208 See Michael Rutter, Psychosocial Resilience and Protective Mechanisms, in Risk and protective factors in the development of psychopathology 97, 97 (Jon Rolf et al. eds., 1990). Howard B. Kaplan, a sociologist at Texas A&M University, emphasizes the difficulties in defining, applying, and manipulating resiliency theory. See Howard B. Kaplan, Toward an Understanding of Resiliency: A Critical Review of Definitions and Models, in Resilience and Development, supra note 12. He first queries whether resilience is an outcome or a factor that influences the outcome: is resilience the good outcome stemming from an at-risk situation, or does it represent the qualities that enable an individual to effect a good outcome? See id. at 19–23. As other experts have noted, such “[d]efinitional diversity results in sometimes disparate profiles of competent adaptation as well as in different estimates of rates of resilience among similar groups.” See id. at 23. Kaplan also warns that resiliency theory necessarily encompasses normative judgments regarding what constitutes risk factors, desirable outcomes, and developmental milestones. See id. at 30–31.
209 See Kaplan, supra note 208, at 23.
210 Id. at 30 (quoting L.C. Rigsby, The Americanization of Resilience: Deconstructing Research Practice, in Educational resilience in inner-city America 85, 85 (Margaret C. Wang & Edmund W. Gordon eds., 1994)).
211 See Kaplan, supra note 208, at 23.
212 See, e.g., Emmy E. Werner & Ruth S. Smith, Vulnerable But Invincible: A Longitudinal Study of Resilient Children and Youth 154–55 (1982); Glantz & Sloboda, supra note 13, at 109, 114–15. According to Kaplan, “risk” has been used to refer to likely negative outcomes, to specific early predictors of later unfavorable outcomes, and as a descriptive term for negative life conditions. See Kaplan, supra note 208, at 36. Kaplan notes that there are two ways to define protective factors: “as individual or environmental characteristics that reflect the absence of risk factors or the presence of ameliorative factors, and, as variables that mitigate the effects of risk factors or strengthen ameliorative effects.” Id. at 46. The latter definition is the more widely accepted definition. See id.
213 Kaplan, supra note 208, at 37.
214 See Glantz & Sloboda, supra note 13, at 115.
215 Although resiliency theory can be used for social justice, as in this Note, there is also a controversial political risk in recognizing “built-in defenses” in children. See Gelman, supra note 16, at 44, 46–47. Politically conservative groups, advocating fewer federal social services, have seized the notion of resiliency to demonstrate that people can overcome poverty without federal aid. See id. Lisbeth Schorr, a lecturer in social medicine at the Harvard Medical School, explains that “[t]he conservative argument against interventions like Operation Head Start and family-support programs is that if these inner-city kids and families just showed a little grit they would pull themselves up by their own bootstraps.” See id. at 47.
216 See Glantz & Sloboda, supra note 13, at 114–15.
217 See generally Werner & Smith, supra note 212.
218 See Terence Monmaney, Kids Who Bounce Back, Newsweek, Sept. 12, 1988, at 67.
219 See id.
220 Werner & Smith, supra note 212, at 155.
221 See Gelman, supra note 16, at 44, 47.
222 See Glantz & Sloboda, supra note 13, at 114–15; supra Section III.
223 See Glantz & Sloboda, supra note 13, at 114–15.
224 See Werner & Smith, supra note 212, at 155; Glantz & Sloboda, supra note 13, at 114–15.
225 See, e.g., Anthony, supra note 15, at 10–11.
226 See generally Werner & Smith, supra note 212.
227 See, e.g., Bulala v. Boyd, 389 S.E.2d 670, 678 (Va. 1990).
228 See Athridge v. Iglesias, 950 F. Supp. 1187, 1192–93 (D.D.C. 1996); Armentrout v. Virginian Railway Co., 72 F. Supp. 997, 1001 (S.D. W. Va. 1947); Bulala, 389 S.E.2d at 677–78.
229 See Glantz & Sloboda, supra note 13, at 114–15.
230 See supra Section III(A).
231 See Chamallas, Architecture of Bias, supra note 6, at 487. See generally Gelman, supra note 16.
232 See Gelman, supra note 16, at 44, 46–47.
233 See id. at 47.