Burney v. City of Pawtucket

559 F. Supp. 1089, 34 Fair Empl. Prac. Cas. (BNA) 1274, 1983 U.S. Dist. LEXIS 18713

• Court: District Court, D. Rhode Island
• Decided: March 9, 1983
• Docket: Civ. A. 82-0817S
• Status: Published

Opinion

OPINION

SELYA, District Judge.

This action for declaratory and injunctive relief and for damages was commenced on December 29, 1982. The original complaint in four counts alleged that defendants, the City of Pawtucket (“Pawtucket”) and three officials of the Rhode Island Municipal Police Academy (“Academy”) discriminated against the plaintiff on the basis of her sex in violation of Title VII, 42 U.S.C. § 2000e et seq., as amended (“Title VII”), 42 U.S.C. § 1983, and the Equal Protection Clause of the Fourteenth Amendment to the United States Constitution; denied her due process of law in violation of 42 U.S.C. § 1983 and the Due Process Clause of the Fourteenth Amendment to the United States Constitution; and denied her rights under Rhode Island law. The facts described in plaintiff’s verified complaint centered about the physical training program and demerit system instituted by the Academy and her consequent loss of employment with Pawtucket due to alleged failure to meet the requirements of the physical training program as evidenced by her accumulation of excessive demerits.

At a hearing held on December-29, 1982, the Court granted plaintiff’s motion for a temporary restraining order and ordered that plaintiff be reinstated in the Academy program pending further order of the Court. Extensive discovery ensued. The Court, inter alia, granted plaintiff’s motion to amend her complaint. The amended complaint added the Academy as a party defendant, and also added a fifth statement of claim challenging the Post Physical Performance Test (“POST-Test”) as discriminating against plaintiff on the basis of her gender in violation of Title VII. The case was reached for hearing on February 11, 1983.

The Court, with the concurrence of counsel, ordered the hearing on preliminary injunction merged with trial on the merits pursuant to the provisions of Rule 65(a)(2), Fed.R.Civ.P. Plaintiff elected to waive all claims set forth in the amended complaint except for those embodied in Count II 1 and Count V 2 thereof, both of which alleged violations of Title VII. Following the trial, decision was reserved.

I.

The underlying facts are. not seriously disputed, although controversy rages unabated concerning the inferences to be drawn from those facts and the legal ramifications thereof. The Court finds that the following facts have been established in this action.

The plaintiff, Gail Burney, a twenty-one year old woman, is a resident of Pawtucket and a high school graduate. Since she was a youngster, she has aspired to be a police officer. Upon graduation from high school, she enrolled at Bryant College and entered its law enforcément program. She has at various times since her graduation applied for vacancies on the police forces of several Rhode Island communities, including her home city.

• The procedure for becoming a Pawtucket police officer is substantially as follows. The applicant must be (i) at least 18 years old, (ii) a United States citizen, and (iii) in possession of a high school diploma or its equivalent. Written and oral examinations are then administered by Pawtucket. Successful applicants, i.e., those ranking highest on the basis of their combined written and oral scores, are sent to the Academy to undergo a pre-admission physical agility test (the “Pre-Test”). Each aspirant is also required to submit to a physical examination, take a psychological test, pass a criminal record check and undergo other screening. If all of the foregoing proceeds without incident, the candidate is then enrolled in the Academy. The sponsoring municipality (in this case, Pawtucket) is the recruit’s employer of record during his or her tenure at the Academy, and pays the recruit a regular weekly stipend.

The Academy was established by the Rhode Island General Assembly in 1969. R.I.G.L. § 42-28.2-2. A Commission on Standards and Training (“Commission”) was established by R.I.G.L. § 42-28.2-3 to fix standards for admission to, and graduation from, the Academy. Defendant Tocco is the incumbent chairman of the Commission. The Commission prepares and publishes mandatory training standards to govern the recruitment, selection and appointment of police officers for all municipal police departments within the State of Rhode Island, excluding only the City of Providence. R.I.G.L. § 42-28.2-8. The Commission is further empowered and directed to establish minimum police training requirements. R.I.G.L. § 42-28.2-8(e). Under Rhode Island law, plaintiff must successfully complete the course and graduate from the Academy in order to be employed as a police officer.

The Academy’s first class was enrolled in August of 1970. From 1971 through 1975, the Academy graduated two classes per year. 3 The first female applicant was admitted in 1975., A total of twenty-six women have graduated from the Academy since that time. In 1976, the Academy began recording grades for physical education, which were included in a recruit’s academic average.

In 1981, plaintiff applied to become a member of the Pawtucket police force. She performed well on the written and oral examinations, but failed the Pre-Test. During the following year, she engaged in a self-structured program of physical development in order to enhance her chances of passing the Pre-Test.

In August of 1982, Pawtucket again invited applications for the position of police officer. Plaintiff applied in response to these advertisements. She ranked seventh after taking the oral and written examinations, passed the Pre-Test, and completed the remaining pre-enrollment screening with satisfactory results. On December 16, 1982, she reported to the Academy. She was the only woman in the class of 1983-1. Upon her enrollment in the Academy, plaintiff became a civilian employee of Pawtucket and began receiving a salary. She must satisfactorily complete the course at the Academy and graduate therefrom in order to remain a municipal employee and to be installed as a member of the Pawtucket police force.

Not only must a recruit pass each course at the Academy including the physical training course in order to graduate, but his or her badge number (which determines seniority at the local police level) is awarded on the basis of class standing. Thus, if two Pawtucket recruits graduate from the Academy’s class of 1983-1, their overall class standing in relation to one another will determine the order in which they are awarded their badge numbers and seniority. Once in police mufti, seniority is instrumental in determining preference on shifts, vacations, extra duty, and the like. A recruit’s grade in physical training accounts for one-fifth of his or her grade in physical education, which in turn represents one-fourth of the individual’s overall academic average at the Academy.

The physical training program currently in effect and its concomitant merit/demerit paradigm were instituted for the first time with the class of 1982-III. There were no women in that class. Thus, plaintiff is the first woman to participate in the current physical training program.

We turn now to an analysis of the physical training program, in all its aspects.

The Academy originally retained Dr. Robert Sonstroem, a professor of physical ■ education at the University of Rhode Island, 4 to synthesize the Pre-Test. The PreTest was first administered in June of 1976 as an entry-level test. As originally fashioned, the Pre-Test had eight subparts; it was later refined and reduced to the present seven components. Prior to the completion of the validation study in 1979, the Pre-Test was administered to candidates for the Academy, but no one was actually rejected due to failure to achieve the entry level. As it now stands, the PreTest consists of seven subparts: percentage of body fat, 1.5 mile run, lift-and-carry, bar dips, flex arm-hang, situps and standing long/broad jump. For purposes of the PreTest, each subtest is accorded equal weight. It is necessary to pass five out of the seven subtests in order to satisfy the requirements of the Pre-Test and to gain admittance to the Academy.

In devising the rejection level for each of the seven subparts on the Pre-Test, Sonstroem utilized a standard of roughly one standard deviation below the mean (average) for men. One standard deviation below the mean for men is also the 15th percentile for masculine performance, so that one would expect 85 percent of all men to pass the Pre-Test. The physical abilities of men as a group and women as a group do, of course, differ; Sonstroem stated that, in deference to these gender-based differences, he would .expect no more than 40 percent of the women participating in the Pre-Test successfully to withstand its rigors. 5

Sonstroem attempted to perform a criterion-related validity study of the Pre-Test in March and April, 1979, and submitted his report validating the paradigm in August of that year. R. Sonstroem, Validation Study: Physical Performance Inventory for Police Officers (August 1979) (“Validation Study”). According to the Uniform Guidelines on Employee Selection Procedures adopted by the EEOC in 1978 (“Guidelines”), 29 C.F.R. § 1607 et seq., criterion-related validity must be “demonstrated by empirical data showing that the selection procedure is predictive of or significantly correlated with important elements of work behavior.” Id. at § 1607.16F.

Rather than relying on the technical standards set forth in the Guidelines (with which he admittedly was unfamiliar), Sonstroem concocted his own techniques. He used a sample size of thirty-six, all of whom were male. His report failed to document the method he used in obtaining this sample; he admitted in his testimony that he could not presently identify the precaution (if any) taken to insure control. He extra polated no data on the number of incumbent police officers, their agencies, average ages and seniority, their distribution by race and sex, or their educational backgrounds, believing that such information was not important. He could not state that his sample was representative of the total population of candidates available for the job, id. at § 1607.14B(4), in terms of those factors, but based on his own “perceptions”, he was sure that departures, other than age, were not great.

Sonstroem failed to carry out a formal job analysis in conducting his validation study. Instead, he informally interviewed police chiefs, Academy personnel and fewer than ten incumbents (chosen from approximately six agencies)! He then administered a “Patrol Action Questionnaire” (“PAQ”) to thirteen police chiefs and supervisors. The PAQ contained fourteen questions, of which the following are prototypical:

4. Patrolman Action: Possessing an arrest warrant, and, after right of entry has been refused, break down a door to gain entrance into a residence that suspect was just seen entering.

& SjS ífc Sfc

11, Patrolman Action: Settle boundary dispute between two angry neighbors by taking appropriate. measurements.

One of four responses could be given to each question:

(i) this action is required of a patrolman;

(ii) this action is expected of a patrolman;

(iii) this action is a matter of individual discretion;

(iv) this action would not be expected of a patrolman.

Validation Study, Appendix C.

The rating scale used by Sonstroem in assessing responses to the PAQ was not designed to ascertain the importance of the various tasks, the consequences of error associated with failure to perform, the time spent in performing each duty, or the relative importance of physical attributes and accomplishments vis-a-vis other functions carried out by police officers. He agreed that the PAQ did not identify the amount of strength or type of strength necessary to perform each of the tasks listed as “important” by the raters. Sonstroem relied instead on his perception that it was “evident that strength is required” for police work, although he agreed that “there are many ways” to perform physical tasks. He did not attempt to determine whether some police officers may not require any appreciable physical fitness to handle the job, nor whether there may be other traits which could compensate for lack of physical fitness.

With respect to the cut-off scores established for the Pre-Test, Sonstroem conceded that they were fairly arbitrary and were not derived either from the results of the validation study or from any meaningful assessment of the minimum level for successful job performance. He defended this glaring lack of empirical evidence by, as he described it, “being lenient” on the PreTest. 6 Of the seven subparts of the PreTest, only two (long/broad jumps, bar dips) showed any across-the-board correlation with high supervisor ratings. Neither body fat nor sit-ups reflected any such correlation, but Sonstroem testified that he kept them in the test to “help” women. In his report, however, he recommended that these subtests be retained because “[b]ody fat is too valid an indicator of health status to discard lightly” and “sit-ups is [sic] the ... third best predictor of academic average at the Academy.” Validation Study at 26. It should be mentioned that whereas Ronald Clare, a personnel psychologist employed by the State of Rhode Island, testified as a part of the defense case, Clare offered no insight into the adequacy of the Validation Study. He had not, in point of fact, ever reviewed it.

In his study, Sonstroem reported a progressive decline in physical performance correlative with age and with passage of time from completion of Academy training. This finding was “not unexpected,” but “it is important to consider that modern patrol function is essentially of a sedentary nature.” Validation Study at 30. Sonstroem therefore anticipated that some police officers in patrolman rank could not presently pass the Pre-Test but were nonetheless performing the job. Although he restricted his sample to relatively youthful males, he noted a significant correlation between supervisor performance ratings and seniority, indicating that the incidence of favorable job performance would increase with age despite progressively declining physical ability. Id. at 31.

The physical training course at the Academy is based on the Pre-Test. A separate grade for this course was not recorded by the Academy until the class of 1979 — 11, roughly coincident with the engagement by the Academy of defendant Shibley as Training Coordinator. 7

The calisthenics and their number, the distance runs and their length and expected times, and the entire structure of the physical training program is described at length in the exhibits. 8 This program is the joint handiwork of Shibley and Sonstroem, and Sonstroem admitted that the performance level on this training program is higher than that set for the Pre-Test. No formal validation study was conducted of the physical training program, nor did Sonstroem conduct any review assessing the program’s minimum performance requirements. A demerit is levied each time a recruit fails to perform the stipulated number of calisthenics or to run the specified distance in the maximum time alloted. Additionally, demerits are assessed for failure to perform calisthenic exercises in unison with the rest of the class as determined by a cadence. 9 The cadence is called out by different recruits selected from time to time by Shibley, and varies accordingly. Only one demerit per exercise per day can be imposed. A recruit who accumulates 20 demerits will be dismissed from the Academy. Sonstroem was aware of the demerit system, but had no role in determining that dismissal would result from an accumulation of 20 demerits.

Requiring women to perform in unison with men appears to have an impact over and above the male/female disparity in physical abilities. The plaintiff, for example, has demonstrated the ability to perform 25 pushups continuously, at her own pace, while she has been unable to do so when required to adhere to the class cadence. Plaintiff’s testimony is credible that the only times she has been assessed demerits for sit-ups occurred when a rapid meter was employed.

Although the POST-Test replicates activities on the Pre-Test, the grading scale, is different. In the Pre-Test, each of the seven subparts carries an equal weight. In the POST-Test, the subparts are weighted as follows: 1.5 mile run — 30%, body fat — 20%, five motor items — 10% each. Instead of a pass/fail system, a letter grade, dependent upon total point accumulation, is assigned. The letter grade represents one-half of the grade in the physical training course. The weighting scale was conceived based solely upon (i) performance of classes at the Academy prior to 1979, and (ii) the proportion of class time spent at the Academy on each activity. The POST-Test grades were originated in January 1979, that is, prior to the time Sonstroem conducted the Validation Study of the Pre-Test (August 1979). No additional validation study , was done, nor was any study carried out of minimum performance levels required by the grading standards.

In order to graduate from the Academy, a recruit must score at the “C” level (70 or better) in each course. Shibley testified that half of the physical training grade is subjective and is based on his observation of each recruit’s achievement and attitude during the Academy session. Demerits are, in his view, merely indicative of these “intangible” factors. Thus, the ultimate grade for physical prowess is an amalgam of the POST-Test scores and of this subjective component.

Sonstroem candidly acknowledged that the differences in physical abilities of men as a group as compared to women as a group make it more difficult for women to perform the Pre-Test, POST-Test, and physical training program, and each of them. 10 With respect to overall measures of strength, women as a group achieve 70% of the values of men as a group. In addition, with respect to upper body strength, women as a group achieve approximately 50% of the values of men as a group. Pushups, bar dips, flex arm-hangs and the lift- and-carry all measure, to some extent, upper body strength. The aerobic capacity of women is in general less than that of men, in approximately the same ratio as overall strength variances. Aerobic capacity is, among other things, a measurement of endurance, the ability to engage in long-term, sustained activity. Thus, women fatigue faster than men; it would be more difficult, on the average, for a woman to complete a 90-minute physical exercise program than for a comparably trained man. Requiring women to perform exercises in syncopation with men renders the women’s ability to perform those exercises even more difficult if the speed at which the exercises are performed is too rapid.

The statistical data as to the Pre-Test, physical training program, POST-Test and course grade confirms Sonstroem’s testimony regarding comparative physical prowess.

The Academy’s records indicate that, of the 41 Pre-Tests administered to women since 1976, there were 20 passing grades (a pass rate of 48.8%). During this same period, 569 Pre-Tests were undertaken by men and 90.5% of them achieved entry level. For the ten Pre-Tests administered since Shibley became training coordinator (PreTests for 1980-1 through 1983-1), the pass rate for women has been 50% (14 out of 28) as contrasted to 90% for men (349 out of 384).

POST-Test results indicate that the pass rate (C or better) for females on this test alone has been 76.9%, as compared to a pass rate of 96.2% for males. The average grade in physical training for female graduates of the Academy was 76.8, compared to an average grade for male graduates of 86.4. Of the 17 women graduates awarded a grade in physical training, 16 failed to earn a grade equal to the average grade for men in their respective classes.

Not a single recruit who has completed the Academy program since the class of 1980-11 (when this grading system was adopted) has received a failing score in physical training, and, as a result, no one has been dismissed from the Academy on that basis. At least one man and two women who scored failing grades on the POST-Test received grades from Shibley, in his subjective evaluation, which brought them up to par.

II.

With this background as to the physical training program at the Academy, we next examine how the plaintiff fared after her enrollment in December of 1982.

By December 27, 1982, the plaintiff had accumulated 12 demerits, all but one for failure to meet the minimum requirements of the physical training program. She was summoned to meet with Shibley and with defendant Shannon (the Academy’s Executive Director). She was informed that, since she was unable to keep up with the physical training program, she would be dismissed unless she acquiesced in a voluntary withdrawal. Shannon explained that those who had withdrawn in the past had been readmitted to the Academy program if returned by their sponsoring agencies, whereas dismissal would leave open no such option. Shannon insisted on an immediate answer, stating in substance that if plaintiff did not resign at that time, she would be dismissed. Plaintiff signed a resignation form which Shannon and Shibley tendered to her.

The next day, plaintiff informed Shannon that her resignation had not been voluntary, that it was rescinded, and that she was reporting for training. Shannon refused to readmit her. At the time she sought readmission, plaintiff had missed only a half-day of the program. 11 The instant action ensued.

As noted earlier, plaintiff has elected to proceed to trial exclusively on Count II and Count V of her amended complaint, alleging in substance that the defendants’ use of the physical training program, the demerit system, and the POST-Test to determine whether or not plaintiff will graduate from the Academy and to determine, in part, her rank or standing within her class upon graduation from the Academy, discriminate against plaintiff on the basis of her sex in violation of Title VII because such tests and selection devices by their very nature disproportionately and adversely affect women.

The Court can expeditiously dispose of the controversy as to the characterization of plaintiff’s departure from the Academy. Whether styled as a resignation or as a dismissal, this separation from service was in no way voluntary. The Court finds that plaintiff was constructively discharged. A constructive discharge has been said to occur when an employer deliberately renders an employee’s working conditions so intolerable that the employee is compelled to resign. Pittman v. Hattiesburg Municipal Separate School District, 644 F.2d 1071, 1077 (5th Cir.1981). The question is whether or not a reasonable person in the employee’s position and circumstances would have felt forced to leave. Id.

The instant case is, viewed most favorably to the defendants, a classic example of constructive discharge. The plaintiff was peremptorily summoned to meet with two ranking officials of the Academy (the Executive Director and the Training Coordinator), who told her that she would be dismissed if she did not resign. They also told her, in effect, that if she was dismissed, she would forfeit any chance ever to become a municipal police officer. Her request for a limited period of time to think about her decision was summarily denied. She was abruptly placed between the frying pan and the fire, and instructed to jump. Under these circumstances, she had no real choice but to resign. Her attempt to rescind her “resignation” on the very next day, after she had an opportunity to secure legal advice, was rejected out of hand. Her termination must, in view of the evidence, be regarded as involuntary.

III.

It is as obvious as an arna in the courtroom that plaintiff has standing to challenge the physical training program. Fifty percent of her grade in physical training will be predicated on her performance in the training program, and she needs a C or better in this course in order to graduate from the Academy. Plaintiff, for like reasons, undeniably has standing to challenge the POST-Test. There is a domino simulacrum here: the plaintiff’s achievements in the training regimen and on the POST-Test will, in material part, determine her physical education course grade; that grade, in turn, will affect her overall average; her average will determine whether she graduates; and, if she does, it will also influence her seniority rights as a Pawtucket police officer. Plaintiff has sustained and is in immediate danger of sustaining direct injury from the physical training program and POST-Test. She fulfils the constitutional requirements for standing. O’Shea v. Littleton, 414 U.S. 488, 493-94, 94 S.Ct. 669, 674-75, 38 L.Ed.2d 674 (1974); Harris v. White, 479 F.Supp. 996, 1006 (D.Mass.1979). Moreover, the injury she alleges is precisely the type of injury which Title VII is structured to prevent. See Griggs v. Duke Power Co., 401 U.S. 424, 91 S.Ct. 849, 28 L.Ed.2d 158 (1971). 12

In Griggs, the Supreme Court held that Title VII, and more particularly 42 U.S.C. § 2000e-2(h), 13 forbids the use of employment “practices, procedures, or tests neutral on their face, and even neutral in terms of intent” if they are discriminatory in effect. Id. at 430, 91 S.Ct. at 853. The Court explained:

Nothing in the Act precludes the use of testing or measuring procedures; obviously they are useful. What Congress has forbidden is giving these devices and mechanisms controlling force unless they are demonstrably a reasonable measure of job performance. Congress has not commanded that the less qualified be preferred over the better qualified simply because of minority origins. Far from disparaging job qualifications as such, Congress has made such qualifications the controlling factor, so that race, religion, nationality, and sex become irrelevant. What Congress has commanded is that any tests used must measure the person for the job and not the person in the abstract.

Id. at 436, 91 S.Ct. at 856. Title VII, in its safeguarding of employment access, wisely emphasizes equality of opportunity and the elimination of discriminatory barriers to professional development. Connecticut v. Teal, - U.S. -, -, 102 S.Ct. 2525, 2530, 73 L.Ed.2d 130 (1982).

In a disparate impact claim such as that here at bar, a tripartite analysis must be applied. To establish a prima facie case of discrimination, plaintiff must show that the facially neutral employment practices which she challenges have a significantly discriminatory impact. Id. If she succeeds in this endeavor, defendants must then demonstrate, by a preponderance of the evidence, that “any given requirement [has] a manifest relationship to the employment in question” in order to avert a finding of discrimination. Id.; citing Griggs v. Duke Power Co., 401 U.S. at 432, 91 S.Ct. at 854. Even if defendant produces such evidence, plaintiff may still prevail by persuading the finder of facts that .the practice in question was a mere pretext for discrimination. Connecticut v. Teal, - U.S. at -, 102 S.Ct. at 2530.

A.

The selection devices at issue in this case are the physical agility requirements of the Academy: the physical training program/demerit system, the POST-Test, the requirement that the recruit obtain a passing mark in physical training in order to graduate, and the inclusion of the physical training grade in computing academic average. The individual components of these physical agility requirements — the seven subparts enumerated ante — are the same components which, in the aggregate, comprise the Pre-Test.

That the Pre-Test has an adverse disparate impact on women is so clear as to be virtually transparent: pass rates are 50% for women as compared to 90% for men, or 55.6% of the pass rate for men. 14 Sonstroem and plaintiff’s expert, Dr. Gerald Kesselman, agreed that the tasks tested in the Pre-Test have a significant adverse impact on women in an even-footed comparison with men. As the physical training program at the Academy, including the demerit system, the POST-Test and the required grades for physical training (which are also included in overall academic average) are founded on the same components as the Pre-Test, reason impels the conclusion that these latter aspects of the physical training program must likewise ineluctably be productive of severe adverse impact on females. Moreover, the evidence abundantly demonstrates that the physical training program (especially the use of lively cadences and the ancillary imposition of demerits for inability to keep up) and the POST-Test have a substantial adverse impact on women, more so than the Pre-Test. A comparison of the rejection levels for the Pre-Test with the point scale for the POST-Test reveals that a man who performed at the minimum task levels on the Pre-Test, but no better, would obtain 16 points, or a failing grade, on the POST-Test, and a woman who performed at the same levels on the POST-Test would obtain 14 points (because of the body fat differential), also a failing grade. 15 Given Sonstroem’s testimony that the Pre-Test rejection level was set at the 15th percentile for men, this comparison highlights that the pass rate for the POST-Test is set at a much higher level than the 15th percentile for men; and that it is correspondingly more difficult for women to pass.

Based on the overwhelming weight of the testimony of the experts (much of which stands uncontroverted), the lay testimony in the case, and the statistical evidence, this Court concludes that plaintiff has convincingly established a prima facie case, and has proved that the physical agility requirements of the Academy as a whole have a disproportionate, adverse impact on women. See Boston Chapter N.A.A.C.P., Inc. v. Beecher, 504 F.2d 1017, 1021 (1st Cir.1974), cert. denied, 421 U.S. 910, 95 S.Ct. 1561, 43 L.Ed.2d 775 (1975).

Defendants argue that there can be no claim of adverse impact from the Academy’s physical agility requirements since all of the women who have entered the Academy subsequent to the institution of the POST-Test in 1979 have graduated. They acknowledge that the POST-Test scores of these women were lower on the average than their final grades, but point out that these scores did not preclude any women from graduating at or near the top of their respective classes. 16

While this contention has a certain superficial appeal, it is essentially an exercise in sophistry. Such “bottom line” justifications have been flatly rejected by the Supreme Court in Connecticut v. Teal, - U.S. -, 102 S.Ct. 2525, 73 L.Ed.2d 130, and by the First Circuit in Costa v. Markey, 694 F.2d 876 (1st Cir.1982). In Connecticut v. Teal, a test required for promotion to a supervisory position within Connecticut’s Department of Income Maintenance was held to have had an adverse impact on black employees notwithstanding that the overall result of the promotion process was more favorable to blacks than whites. The state’s exhortation that absence of overt discrimination at the “bottom line” foreclosed the employees from establishing a prima facie case, or, in the alternative, that it provided an absolute defense, was found wanting. The Court demonstrated that,

The suggestion that disparate impact should be measured only at the bottom line ignores the fact that Title VII guarantees these individual respondents the opportunity to compete equally with [male] workers on the basis of job-related criteria. Title VII strives to achieve equality of opportunity by rooting out “artificial, arbitrary and unnecessary” employer-created barriers to professional development that have a discriminatory impact upon individuals.

Id. at -, 102 S.Ct. at 2533. The Court concluded that the claim of disparate impact from a pass-fail barrier to employment opportunity stated a prima facie case of employment discrimination under 42 U.S.C. § 2000e-2(h) regardless of the “bottom line”. Id.

The First Circuit applied this reasoning in Costa v. Markey, 694 F.2d at 880. There, the Court of Appeals held that the plaintiff established a prima facie case of disparate impact discrimination in showing that the employer’s height requirement excluded far more women than men from competing for the position of police officer, id., even though the height requirement was applied only to women applicants. Id. at 878.

The teachings of Teal and of Costa are that the end, no matter how pristine, cannot in the context of Title VII justify tainted means. Defendants’ “bottom line” argument is conceptually indistinguishable from the assertions rejected in Teal and in Costa. It must therefore be rejected in this case as well.

Defendants also contend that because the physical training program and POST-Test collectively constitute such an infinitesimal component of a recruit’s academic average, any disparate impact is de minimis. This argument seeks, in effect, to deflect the gender-based bias of the physical gymnastics here at issue by a Byzantine exercise of mental gymnastics which, stripped of all trappings, says to the Court: yes, we did— but so what? The asseveration blithely ignores the fact that failure to fulfill any of these requirements can lead to either dismissal from the Academy or failure to graduate. One need not tromp very far afield in search of apt illustrations of this point. In the case at bar, plaintiff was dismissed for accumulating excessive demerits in the physical training program. Any stricture which contains within its purview the ready potential for such decisive consequences cannot be de minimis, albeit that requirement is but one of many.

B.

As plaintiff has proven her prima facie case, the burden shifts to the defendants to produce credible evidence that the Academy’s physical agility requirements “have a manifest relationship to the employment in question.” Griggs v. Duke Power Co., 401 U.S. at 432, 91 S.Ct. at 854. The First Circuit has brought the matter into sharp focus:

[W]hat is at issue is whether [these requirements] demonstrably select[] people who will perform better the required on-the-job behaviors after they have been hired and trained. The crucial fit is ... between the test and job performance.

Boston Chapter N.A.A.C.P., Inc. v. Beecher, 504 F.2d at 1021-22.

The conventional approach to sustaining this burden involves an exegetic demonstration that the selection devices in issue have been validated by scientifically acceptable methodology. Albemarle Paper Co. v. Moody, 422 U.S. 405, 431, 95 S.Ct. 2362, 2378, 45 L.Ed.2d 280 (1975). The Guidelines, which draw heavily upon professional standards of test validation established by the APA, set forth detailed criteria for authenticating selection devices and have been accorded great deference by the courts in determining whether an employer has met its Title VII obligations. E.g., id.; Guardians Association of the New York City Police Department, Inc. v. Civil Service Commission, 630 F.2d 79, 91 (2d Cir.1980), cert. denied, 452 U.S. 940, 101 S.Ct. 3083, 69 L.Ed.2d 954 (1981) (“Guardians IV’); Boston Chapter N.A.A.C.P., Inc. v. Beecher, 504 F.2d at 1024.

Generally, the employer may use any of three methods to validate a selection device:’ (i) criterion validity, (ii) construct validity, or (iii) content validity. See Guidelines, 29 C.F.R. § 1607.5. Criterion validity compares impartial evaluations of employees’ job performances with test scores. Construct validity ascertains the degree to which applicants possess traits reasonably considered salient for job-related purposes. Content validity assesses meaningfully ability to perform specific occupational tasks. Id. See Harless v. Duck, 619 F.2d 611, 616 n. 5 (6th Cir.), cert. denied, 449 U.S. 872, 101 S.Ct. 212, 66 L.Ed.2d 92 (1980).

The situation here is unorthodox in that the defendants made no perceptible effort to validate, by any acceptable professional method, the physical training course, the demerit system, or the POST-Test. Defendants admitted that no study whatsoever was carried out anent any of the foregoing. At trial, counsel for the defendants attempted creatively to construct a ease for the entire physical training schemata at the Academy including the POST-Test and graduation requirements, upon a foundation of pragmatic building blocks such as “human experience” and “experience of police officers on the job”. The architecture of the argument is that this experiential knowledge can be used to prove that doing a certain “number of pushups” is part of the necessary training for police officers “for as far back as anyone can remember.” This crude ichnography, however, must topple from its own weight. It amounts to little more than a declamation that physical training requirements are appropriate because they appear appropriate. Such a substitution of instinct for hard proof is convenient, but totally lacking in legal merit. As noted in Berkman v. City of New York, 536 F.Supp. 177 (E.D.N.Y.1982), “while the concept of face validity may have some public relations role ..., face validity is no substitute for validation based on concrete analysis either of the job’s requirements or the test’s results.” Id. at 207.

Neither can defendants rely on Sonstroem’s “validation” of the Pre-Test to confirm the physical training course, the demerit system, or the POST-Test. Kesselman testified, and the Court finds, that such an assumption would be at variance with professional standards because the physical training program is not identical to the Pre-Test. 17 Such piggy-backing would also be contrary to the Guidelines, 29 C.F.R. § 1607.9A, and to the Supreme Court’s ruling in Albemarle Paper Co. v. Moody, 422 U.S. at 431, 95 S.Ct. at 2378. The physical training program consists of different exercises than the Pre-Test. The POST-Test does utilize the same elements as the PreTest but they are weighted differently and used to award a grade or rank. The cut-off scores on the POST-Test do not pretend to be supported by the Pre-Test validation study.

Moreover, the Validation Study is wholly deficient when measured against either the Guidelines or the often under-utilized yardstick of common sense. 18

Sonstroem testified that this was a criterion-related study. The Guidelines at 29 C.F.R. §.§ 1607.14B and 1607.15B set forth in great detail the standards and documentation necessary for such a study. Sonstroem’s work-up failed to effect substantial compliance with these. First, his sample of thirty-six male incumbent police officers was too scanty and could not fairly be said to be representative of the population to be studied. Id. at § 1607.14B(1) and B(4). Secondly, Sonstroem failed to obtain any statistically significant correlation between achievement on the Pre-Test and occupational performance. 19 See Boston Chapter N.A.A.C.P., Inc. v. Beecher, 504 F.2d at 1024, 1024 n. 13.; 29 C.F.R. § 1607.14B(5). More importantly, Sonstroem failed to do any meaningful job analysis as required by the Guidelines. 20 C.F.R. § 1607.15B(3). Such an analysis must contain “a thorough survey of the relative importance of the various skills involved in the job in question and the degree of competency required in regard to each skill.” Vulcan Society v. Civil Service Commission, 360 F.Supp. 1265, 1274 (S.D.N.Y.), aff’d. 490 F.2d 387 (2d Cir.1973). Job functions must be individually identified. The importance of these functions in relation to each other must also be determined. United States v. City of Chicago, 573 F.2d at 426.

The task inventory compiled by Sonstroem (the PAQ), consisted of fourteen generic tasks, each of which could be broken down into discrete functions. 20 No guidance was given as to the precise manner in which an officer was to perform each task. For example, what were the “appropriate measurements” referred to in question 11 of the PAQ, discussed supra? The question is rhetorical, as the answer, if there is one, must be deduced in an entirely subjective fashion. Sonstroem also failed to indicate how the PAQ was developed, contrary to the Guidelines. See 29 C.F.R. § 1607.-15B(3). Moreover, the PAQ was administered only to police chiefs and supervisors, rather than to incumbents, in contradistinction to the accepted professional norm which looks to those actually performing the job as the best and most enlightening source of general information about job functions.

The rating procedure which Sonstroem used failed to chart the criticality or impor-. tance of the various tasks or of the functions within each task. In an analogous vein, the consequences of error were not identified. The Validation Study is silent as to the amount of time spent by police officers in performing each of the duties or tasks delimited by the PAQ, and to relative importance of physical on-the-job performance to other activities clearly required of police officers (such as those which involve cognitive abilities, interpersonal skills and the like).

Finally, Sonstroem’s perscrutation in no way established that physical ability as measured by the Pre-Test was a critical trait for the'position of police officer, nor that without it, one could not adequately serve in the post. As Kesselman testified:

[T]he bottom line is that Dr. Sonstroem, through the lack of an adequate job analysis, was not able to establish the bedrock foundation of the entire study; namely, that physical performance is a critical ability that cannot be compensated for by any other ability, that without this ability, you cannot perform the functions of the job in total.

Kesselman Deposition at 56-57.

In short, the Validation Study relied on by the defendants fails to demonstrate in any manner that any portion of the PreTest “[has] a manifest relationship to the employment in question.” Connecticut v. Teal, - U.S. at -, 102 S.Ct. at 2531; Griggs v. Duke Power Co., 401 U.S. at 432, 91 S.Ct. at 854. As the Supreme Court said of the study at issue in Albemarle Paper Co. v. Moody,

There is no way of knowing precisely what criteria of job performance the supervisors were considering, whether each of the supervisors was considering the same criteria or whether, indeed, any of the supervisors actually applied a focused and stable body of criteria of any kind. There is, in short, simply no way to determine whether the criteria actually considered were sufficiently related to the [employer’s] legitimate interest in job-specific ability to justify a testing system with a ... discriminatory impact.

422 U.S. at 433, 95 S.Ct. at 2379. Since Sonstroem’s Validation Study does not justify the use of the Pre-Test as a prerequisite to police employment, it follows necessarily that the Validation Study cannot be seized upon to uphold other, more remote aspects of the physical training program.

Other findings in the Validation Study cast serious doubt upon use of the Pre-Test as well. Sonstroem found that the physical performance of police officers progressively declined with age and years from the Academy. He admitted that he would therefore expect to find that there are, in the field, incumbents who could not pass the Pre-Test but who are performing the job adequately on a current basis. Although he restricted his sample to men thirty-six years of age or under so as to reduce the impact of seniority, he nonetheless found a high correlation between supervisor ratings and seniority, indicating that ratings would increase with age despite progressively declining physical ability. Kesselman’s exposition of this phenomenon is creditable:

It means even though as physical performance ... deteriorates over time, overall performance judged by supervisory ratings do[es] not deteriorate over time. As a matter of fact, they increase, which would again argue that these police officers, as they get older, are performing the functions of their job acceptably, and even more acceptably, perhaps even in the face of declining physical performance. So they’re compensating. It is quite clear they’re compensating in some other way, or their job functions are such that they don’t require heavy physical performance... It is obvious from this that you can do the job of a police officer effectively without having a tremendous amount of physical fitness.

Kesselman Deposition at 66-67. Thus, the evidence does not support the use of the Pre-Test as a knock-out factor.

Even if the Validation Study had sufficiently authenticated the Pre-Test, Sonstroem acknowledged that he was unable to determine “cut-off scores” on the basis of its results. He therefore arbitrarily extrapolated elimination at the 15th percentile for men. This flies in the teeth of the Guidelines, which require that cut-off scores “be set so as to be reasonable and consistent with normal expectations of acceptable proficiency within the work force.” Guidelines, 29 C.F.R. § 1607.6H.

The foregoing review and explication leads the Court inexorably to the conclusion that defendants have failed to meet their burden of producing credible evidence from which it could be deduced that the physical agility requirements of the Academy “have a manifest relationship to the employment [of police officers].” Griggs v. Duke Power Co., 401 U.S. at 432, 91 S.Ct. at 854. The only remaining question is as to the relief to be accorded to the plaintiff.

IV.

This Court possesses broad power, as a court of equity, to remedy the vestiges of discrimination, once a violation of Title VII has been established. Association Against Discrimination v. City of Bridgeport, 647 F.2d 256, 278 (2d Cir.1981), cert. denied, 455 U.S. 988, 102 S.Ct. 1611, 71 L.Ed.2d 847 (1982); Guardians IV, 630 F.2d at 108. See Castro v. Beecher, 459 F.2d 725, 736 n. 15 (1st Cir.1972). At a minimum, Title VII relief should assure compliance with the law. Guardians IV, 630 F.2d at 108. Relief should also make persons whole for injuries suffered in consequence of discrimination. Albemarle Paper Co. v. Moody, 422 U.S. at 421, 95 S.Ct. at 2373; Costa v. Markey, 694 F.2d at 881.

The scope of relief ordered need not be circumscribed simply because this is an individual Title VII case rather than a class action suit, for the “court has not merely the power but the duty to render a decree which will so far as possible ... bar like discrimination in the future.” Albemarle Paper Co. v. Moody, 422 U.S. at 418, 95 S.Ct. at 2372; Meyer v. Brown & Root Construction Co., 661 F.2d 369, 373 (5th Cir.1981); Taylor v. Jones, 653 F.2d 1193, 1203 (8th Cir.1981). 21

In a disparate impact case such as the instant action, the effectuation of compliance may well necessitate proscription of the use of invalid examinations, specification of procedures and standards for new selection devices, and authorization of suitable interim action to insulate against disparate sexual impact. Association Against Discrimination v. City of Bridgeport, 647 F.2d at 278; Guardians IV, 630 F.2d at 108; Berkman v. City of New York, 536 F.Supp. at 216.

As this Court has found the existing physical agility requirements of the Academy, specifically, the physical training program/demerit system, the POST-Test, the graduation requirement of a minimum grade of 70 in physical training, and the inclusion of the physical training grade in computing overall academic average, to have unlawful disparate repercussions against women, it is appropriate to restrict their use so as to avoid in the future such disparate impact. Guardians IV, 630 F.2d at 108-09; Berkman v. City of New York, 536 F.Supp. at 216-17. It appears from the evidence that the effects of discrimination can largely be eliminated by: (i) dispensing with the demerit system in its present form and with the use of cadences in the physical training program, (ii) deleting the POST-Test as presently compiled as a component of the physical training grade, (iii) deleting the graduation requirement of a minimum grade of 70 in the physical training course as now constituted, and (iv) excluding such physical training grade from computation of the recruit’s overall academic average at the Academy. This Court will, by use of its injunctive powers, mandate these reforms, not only as to the plaintiff but as to all future Academy enrollees. 22

The foregoing anodyne, however, should be viewed as only a temporary palliative. Some physical training undoubtedly is needed for police officers, but this training should be free from taint in all its aspects. See Vulcan Society v. Civil Service Commission, 360 F.Supp. at 1278. Therefore, all defendants, excluding Pawtucket, are directed forthwith to commence preparation of new physical training procedures, validated in general accord with the Guidelines and APA Standards and which have the least practicable adverse impact on women, the same to be completed with all deliberate celerity. Berkman v. City of New York, 536 F.Supp. at 216. See Vulcan Society v. Civil Service Commission, 360 F.Supp. at 1278.

Inasmuch as plaintiff successfully completed the Pre-Test upon her second attempt, the Pre-Test no longer looms as an obstacle in her chosen career path. Nevertheless, it is, in the judgment of this Court, a patently invalid and invidiously discriminatory device. To sanction or to allow its continued use by the Academy would figuratively require the Court to close its eyes and to hold its nose. Such an exercise in ostrichism is anathematie to this Court. Hence, the Court will exercise its equitable powers to declare the use of this test illegal and to bar its future use as it currently stands in selecting police cadets. Defendants, excluding Pawtucket, are directed with all due dispatch to prepare new preentrance physical screening procedures in accordance with the Guidelines and APA Standards, which shall have the least practicable adverse impact on women. Berkman v. City of New York, 536 F.Supp. at 216.

The Court is not blind to the obvious; physical decrepitude at some point must inhibit the proper performance of police duties. 23 The Court recognizes that some rational physical fitness requirements must, accordingly, exist and be enforced if the Academy is to continue to serve its purpose. The Court’s findings and directives, as set forth herein, do not preclude the defendants from adopting and implementing, on an interim basis, non-discriminatory physical qualifications to be applied as a prerequisite to Academy enrollment; nor from adopting and implementing such non-discriminatory qualifications as an interim condition precedent to graduation. Continued maintenance of the physical education program itself is not enjoined, subject of course to the specific limitations upon, and eliminations from, that program as hereinbefore described.

No money damages are awarded to the plaintiff, as her claims for back pay and for compensatory and punitive damages have been waived. Plaintiff’s reinstatement in the Academy, previously effectuated by way of a temporary restraining order issued by this Court, is hereby confirmed; her purported resignation from the Academy is hereby annulled; and her dismissal from the Academy is hereby vacated. There shall be expunged from plaintiff’s record at the Academy any and all references to (i) the demerits heretofore levied against her in the course of the physical training program 24 , and (ii) her dismissal, and (iii) her initial failure to pass the Pre-Test.

V.

The Court does not question the good faith or the intentions of the defendants. The Academy has served with distinction since its creation by the General Assembly and it is a sterling example of beneficial cooperative endeavor between the state and thirty-eight of its municipalities. Shannon, Shibley and Tocco are all dedicated public servants, and are men of significant accomplishment. The federal courts, however, must stand firm as the guardian of rights conferred by Congress upon the citizenry; Title VII, in respect to matters such as those here sub judice, tolerates no exceptions from its sweep for worthiness of motive or for absence of malevolent design.

The plaintiff shall prepare and present to the Court a form of order and injunction consonant with the teachings of this opinion. The plaintiff shall further file with the Court, within thirty days from the date hereof, her application for counsel fees, costs and expenses.

SO ORDERED.

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" width="1537"/>

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" width="1398"/>

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" width="1496"/>

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" width="1339"/>

APPENDIX B

POST Physical Performance Test Grading Standards

RHODE ISLAND MUNICIPAL POLICE TRAINING ACADEMY

HOW TO EARN YOUR PHYSICAL PERFORMANCE GRADE

This improved method of grading physical performance was developed after analyzing final scores of 203 previous Police Academy candidates.

It is based on a stanine scale and awards from 1 to 27 points for your performance at each of the seven sub-tests of the Physical Performance Inventory. Stanine points to

be awarded for all possible scores are presented in Table 2 on page 2. For example, if you performed 42 situps, you would earn 4 stanine points for situps. If your final 1.5 mile time was 10:26, you would earn 18 points at the 1.5 Mile Run. Summing your stanine points across the 7 sub-tests will produce your Composite Fitness Score.

Table 1 explains how many points you will have to earn to achieve your fitness score at the Police Academy.

TABLE 1

Composite Fitness Score

Grade

67 to 90

a

50 to 66

g

32 to 49

c

20 to 31

u

10 to 19

F

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" width="1092"/>

1 . Count II alleges that “Defendants and Pawtucket in dismissing plaintiff from the Police Academy and from employment have discriminated against plaintiff on the basis of her sex in violation of Title VII.” Verified Complaint ¶ 38.

2 . Count V alleges that the POST-Test and the preadmission physical agility test imposed by defendants, which have not been validated and are not job-related, have a disproportionate and adverse impact on women in violation of Title VII. Count V further alleges that defendants discriminate against plaintiff in violation of Title VII by determining whether she will graduate from the Academy and assessing her rank at graduation on the basis of her performance in physical training and oil the POST-Test, both of which have a disproportionate impact on women. Pawtucket, in determining whether plaintiff will remain employed upon the basis of her graduation from the Academy and in basing her seniority upon her class standing at the Academy, violates Title VII. Amendment to Verified Complaint ¶¶ 48-55. It should be noted that Pawtucket, as the employer of record, is virtually a nominal defendant in this action; the city is mandated by state' law to utilize the services of the Academy, and it is the Academy and its officials who have set the rules for the programs and policies here at issue.

3 . Only one class is enrolled at the Academy at a time. The first class which graduates in each year is referred to as, for example, 1976-1, the second class in 1977 as 1977-11, etc.

4 . Sonstroem received a Ph.D. in Educational Psychology in 1968 from the University of Minnesota. He has conducted two validation studies concerning the correlation between an employment or selection device and job performance: a firefighters’ study for East Providence, Rhode Island and the 1979 study for the Academy, discussed infra. He has never conducted a formal written job analysis. He is not a member of the American Psychological Association (“APA”), nor was he familiar with Division 14 thereof, the Division of Industrial and Organizational Psychology, or Division 5, Evaluation and Measurement. Divisions 14 and 5 of the APA specialize in employment testing and validation.

5 . According to Sonstroem, the 15th percentile for men translates roughly to the 60th to 70th percentile for women.

6 . In his report, Sonstroem recommended that “the physical performance capabilities of patrolmen should be improved.” Ex. 8 at 28. He recognized, however, that additional training programs have not yet been implemented. Deposition of Dr. Robert Sonstroem, dated January 14, 1983 (“Sonstroem Deposition I”), at 72.

7 . Shibley had previously served for twelve months as a police officer, patrolman rank, in Arlington County, Virginia. He has a masters degree in Criminal Justice from the John Jay College of Criminal Justice. Prior to his engagement as training coordinator at the Academy, he was executive director for the Rhode Island Police Chiefs’ Association from 1976 to 1979. He has never worked as a police officer in Rhode Island.

8 . The Academy’s “Physical Training Recruit Program” is set forth in Appendix A to this Opinion, and the POST-Test and grading standards are attached as Appendix B.

9 . Shibley testified that the purpose of the cadence is to enable him to keep an accurate count of the exercises so that demerits can be assessed properly. He does not expect the cadence to promote successful performance on the job, although he thought that it promoted leadership qualities as to the person calling the cadence.

10 . Sonstroem “absolutely” agreed that “no matter how generous [the] norms are, it’s going to be harder for women to pass them as a group than men.” (Sonstroem Deposition I, at 15.)

11 . Recruits are allowed five sick-leave days by the Academy.

12 . Plaintiff received her right-to-sue letter on February 2, 1983, after she filed suit seeking temporary relief. The Court had jurisdiction to grant such relief, however, given the exigencies of the situation, the equitable powers of the Court, and the remedial nature of Title VII. Sheehan v. Purolator Courier Corp., 676 F.2d 877 (2d Cir.1982). See Rice v. New England College, 676 F.2d 9 (1st Cir.1982); Black v. Brown University, 555 F.Supp. 880 at 883-84 (D.R.I.1983).

13 . 42 U.S.C. § 2000e-2(h) provides that it shall not “be an unlawful employment practice for an employer ... to give and to act upon the results of any professionally developed ability test provided that such test, its administration or action upon the results is not designed, intended or used to discriminate because of race, color, religion, sex or national origin.”

14 . The Guidelines provide that a selection rate that “is less than [80 percent] of the rate for the group with the highest rate will generally be regarded ... as evidence of adverse impact.” 29 C.F.R. § 1607.4D. See Connecticut v. Teal, - U.S. at - n. 4, 102 S.Ct. at 2529 n. 4.

In determining adverse impact, the Court relies on comparisons of men and women presenting themselves for the Pre-Test and attending the Academy. See Berkman v. City of New York, 536 F.Supp. 177, 206 n. 19 (E.D.N.Y.1982).

15 . This is calculated as follows. Performance at the Pre-Test minimum expected level would receive the following points on the POST-Test: flex-arm hang, 36 seconds — 3 points; standing broad/long jump, 73 inches — 2 points; bar ■dips, 2 — 2 points; lift and carry, 19.0 seconds —1 point; sit-ups, 28 — 1 point; 1.5 mile run, 15 minutes — 3 points; male body fat, 29.9% — 4 points; female body fat 36.9% — 2 points.

16 . At trial, counsel for the defendants emphasized how well women performed at the Academy. Two-thirds of the female graduates had been in the top half of their classes, and two of these women had ranked first in their respective classes. He acknowledged that women did not perform as well as men on the physical agility requirements, but discounted this because “women performed better than men in social science.”

17 . Kesselman’s credentials as an expert in the field of job analysis and testing stand in sharp contrast to Sonstroem’s. Kesselman is a licensed psychologist and member of Division 14 of the APA and familiar with the leading literature in the field. He has authored or co-authored a number of relevant articles. Roughly 70% of his time is devoted to job analysis, test development and validation studies. He has performed approximately 500 job analyses and roughly the same number of validation studies.

18 . Indeed, Sonstroem made no attempt to conform his study with the Guidelines. Defendants’ burden to prove job relatedness is much higher when the Guidelines are ignored. United States v. City of Chicago, 573 F.2d 416, 427 (7th Cir. 1978). There, the Seventh Circuit stat ed that “[c]ompliance with these Guidelines is generally required absent some showing that a cogent reason exists for noncompliance.” Id. See Guardians IV, 630 F.2d at 96; Berkman v. City of New York, 536 F.Supp. at 208. No such showing has been made in the instant case.

19 . Professional Standards and the Guidelines accept a significance level of no greater than .05 (5 chances out of 100 that the results are a matter of chance). Guidelines, 29 C.F.R. § 1607.14B(5); Sonstroem I Deposition at 75,-114. The total correlation coefficient of the Pre-Test as a whole was 0.25. Correlation coefficients of less than .30 are generally considered below practical significance. Boston Chapter N.A.A.C.P., Inc. v. Beecher, 504 F.2d at 1024 n. 13.

20 . Plaintiffs expert testified that:

Numerous studies have been done in the area of police performance, and task lists in the neighborhood of between seventy and a hundred fifty important tasks have been identified in other studies, so it is quite apparent that the fourteen tasks do not represent the total domain of performance in the job of police officer, let alone the demand of physical performance, which is the central concern of this study.

Deposition of Dr. Gerald A. Kesselman, dated January 27, 1983 (“Kesselman Deposition”) at 52.

21 . The language of Title VII empowers the courts to grant a wide variety of relief to combat discriminatory practices. Meyer v. Brown & Root Const. Co., 661 F.2d at 373.

22 . Presumably, plaintiffs rank and therefore seniority on the Pawtucket police force have not yet been affected by the defendants’ discriminatory acts. The Court’s order regarding the elimination of those aspects of the physical training program having a disparate impact will have an immediate benefit only for the plaintiff, as she is the only woman in the Academy’s current class.

23 . On the other hand, the Court must at least take note that the opinion of one respected world leader seemed inclined to discount even this moderate view. Sir Winston Churchill is credited with having written a letter on Feb. 4, 1941 to the Secretary of State for War, reprinted in Churchill, Winston S., The Grand Alliance 730 (Houghton Mifflin Co., 1950), in which he observed:

“In my experience, based on many years’ observation, officers with high athletic qualifications are not usually successful in the higher ranks.”

24 . Any demerits levied against plaintiff for reasons unrelated to the physical training program may stand.