_'chnical Te Rtep A20 .

RELIABILITY OF A JEASURE OF INSTITUTIONAL,

DISCRIMINATION AGAINST MINORITIES- /

DwvightlJ.oehrirtg

ODTIC

~ELECTE11

ARI FIELD UNIT, PRESIDIO OF MONTEREY, CALIFORNIA

U.S. Army

Research Institute for the Behavioral and S Si

i ~ "D ~ ,,t comd=,;,,,, 1079,/

M Approved for public release; distribution unlimited. /00

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V7 T U. S. ARMY RESEARCH INSTITUTE

FOR THE BEHAVIORAL AND SOCIAL SCIENCES

A Field Operating Agency under the Jurisdiction of the

Deputy Chief of Staff for Personnel

FRANKLIN A. HART

JOSEPH ZEIDNER Colonel, US Army Technical Director Commander

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4. TITLE (and Subtltle) S. TYPE OF REPORT & PERIOD COVERED

RELIABILITY OF A MEASURE OF INSTITUTIONAL

DISCRIMINATION AGAINST MINORITIES s. PERFORMING ORG. REPORT NUMBER

7. AUTNORVs) 6. CONTRACT OR GRANT NUMBER(&)

!i Dwight J. Goehring

S. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK

US Army Research Institute for the Behavioral AREA 6 WORK UNIT NUMBERS

and Social Sciences PERI-IO 2QI63744A769

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II. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE

Office of Equal Opportunity Programs DAPE-HRE December 1979

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0 IS. SUPPLEMENTARY NOTES

19. KEY WORDS (Continue on reverse side if necessar nd identify by block number)

Institutional discrimination Women Difference indicator

Discrimination Equal Opportunity Statistics

Minorities Reliability Monte Carlo method

Blacks Measurement

TRACT' (Ctime an ees ebb N metIdeatify derae by block nwimbes) 47

" LThe technical properties of a statistical measure of the e of institutional discrimination are discussed. Two methods of dealing with the

problem of reliability of the measure in small samples are presented. The

first is based upon classical statistical theory and the second derives from

a series of computer-generated Monte Carlo analyses. A test for differences

between the measures is also developed and presented.f

DD I 1473 E fmlWOF INOV 6s IS OBSLETE Unclassified

, SECURITY CLASSIFICATION OF THIS PAGE (10m Data V01te

. .ob.-
Technical Report 429

RELIABILITY OF A MEASURE OF INSTITUTIONAL

DISCRIMINATION AGAINST MINORITIES

Dwight J..Goehring

James A. Thomas, Team Chief

Submitted by:

Jack J. Sternberg, Chief

ARI FIELD UNIT, PRESIDIO OF MONTEREY, CALIFORNIA

Approved by:

E. Ralph Dusek, Director

PERSONNEL AND TRAINING

RESEARCH LABORAOTRY

U.S. ARMY RESEARCH INSTITUTE FOR THE BEHAVIORAL AND SOCIAL SCIENCES

5001 Eisenhower Avenue, Alexandria, Virginia 22333

Office, Deputy Chief of Staff for Personnel

Department of the Army

December 1979

Army Project Number Army Contemporary Issues

20163744A769

* Approved for public release; distribution unlimited.

ii
JREWORD

Since 1972 the Army Research Institute for the Behavioral and

Social Sciences (ARI) has conducted technical research in support of

the Army's Equal Opportunity Program. In 1974 ARI, under contract,

documented the existence of institutional discrimination in the Army.

*The document, published first as ARI Technical Paper 270 and later as

DA PAM 600-43, sets forth a basic measurement system for monitoring

equal opportunity status. ARI technical report TR-78-B13, also developed under contract, adapts the measurement system for use at Major

Command, post, or brigade levels. This report, produced in-house

at the ARI Field Unit at the Presidio of Monterey, California, addresses

specific problems in applying the measurement procedures to relatively

small groups and the possible solutions to such problems. Research was

accomplished in response to requirements of the Office of Equal Opportunity Programs, DAPE-HRE, and to Army Project 2QI63744A769, "Army

Contemporary Issues," FY 1978 Work Program.

Inical Director

I

Arrjio. n For

W.C TAB

juttif icat ion-

, .. V - d

!D st I _ 

a l

V
RELIABILITY OF A MEASURE OF INSTITUTIONAL DISCRIMINATION AGAINST

MINORITIES

BRIEF

Requirement:

To analyze in some detail the statistical properties and general

operating characteristics of a measure of institutional discrimination

against minorities which has been recommended for use at Major Command,

post, or brigade levels.

Procedure:

Both general and computer-assisted analytical procedures were used.

A number of examples are used to clarify the points.

Findings:

The relevant concepts are defined and explained. Complete as

well as short-cut procedures for assessing the reliability of the

measure are presented and discussed.

Utilization of findings:

The information resulting from this research endeavor should enable

both other researchers in the area and general users of the measure to

have a better understanding of its technical ch&racteristics and ultimately make more effective use of it as a management tool.

Vi [5[

" " V-4-

.5 I
RELIABILITY OF A MEASURE OF INSTITUTIONAL DISCRIMINATION AGAINST

MINORITIES

CONTENTS

Page

INTRODUCTION ............ ............................ ... 1

MEASUREMENT OF INSTITUTIONAL DISCRIMINATION .... ............... I

RELIABILITY OF DIFFERENCE INDICATOR VALUES ...... ............. 4

RELIABILITY OF DIFFERENCE INDICATOR DIFFERENCES ..... ........... 6

CONCLUSION ............. ............................. 9

REFERENCES ........... ............................. . .

FIGURES

Figure 1. Numerical Values for Calculating a Difference

Indicator ........... ....................... 5

2. Reiliability of Difference Indicator Values ... ..... 7

TABLES

Table 1. Difference Between Two Difference Indicator Values . 8

-i
RELIABILITY OF A MEASURE OF INSTITUTIONAL DISCRIMINATION AGAINST

MINORITIES

INTRODUCTION

Institutional racism (Knowles and Prewitt, 1969) is generally contrasted with personal racism. The latter can be defined as actions

taken by one or more individuals with intended malice based upon prejudice

against persons of another race. While differing definitions of

institutional racism have been suggested in the literature, here it can

be generally conceptualized as any negative impact upon a specific race

of people resulting from routine operations or procedures of an organization or other suprapersonal structure. These two types of racism are

not unrelated. Indeed, in specific instances, they may be symmetrically

causative. A primary distinction between them is their differing mode

of impact: impersonal compared to personal. To generalize the concept

of institutional racism to institutional discrimination against minorities

requires only the awareness that similar mechanisms may operate against

aggregations of people based upon communalities other than race.

Feagin (1978) distinguishes two types of institutional discrimination: direct, where there is intent to harm the minority group in

question, and indirect, where no intent exists. The indirect variety is

of particular interest. It can develop and operate not only without

intent but without anyone's awareness. Feagin notes that indirect

institutional discrimination has two common forms: side-effect and

past-in-present discrimination. The former is exemplified by the use of

some selection variable, either correlated with performance criteria or

not, which differentially rejects disproportionately large numbers of

minority individuals. Past-in-present discrimination concerns past

inequities or injustices which place minority members at a disadvantage

in some current, ostensibly equitable circumstance involving selection.

MEASUREMENT OF INSTITUTIONAL DISCRIMINATION

A statistic termed the Difference Indicator (D.I.) has been developed under contract for the U.S. Army which can measure institutional

discrimination. It has been applied to a wide range of variables with

specific reference to the status of black American soldiers (DA PAN

600-43). The study found overrepresentation of blacks in areas such as

military justice actions and underrepresentation in areas such as

promotions. The pattern of overrepresentation and underrepresentation

of blacks in the Army at the time of investigation was clearly and

consistently to their disadvantage. The D. I. system has recently been

recommended for use at division and brigade levels (Nordlie, Edmonds &

* Goehring, 1978).

I

1

- _ =.U" =l 
The D.I. takes the general form of a ratio of the proportion

of individuals selected for the category or dimension of interest who

belong to the minority group to the proportion of minority group members

in the eligible population for the category. The ratio is subjected to

a linear transformation, multiplied by 100 minus 100. Thus,

D. I. = 

T x 100 - 100, where (1)

P - the proportion of persons slected for a category who are minority

group members, and

v - the proportion of all eligible persons who are minority group

members.

Under the assumption that all factors leading to category inclusion

are constant between minority and majority group eligibles it follows

that the probability of inclusion in the category is- statistically

independent of group membership. linder this assumption it can be shown

that the expected value of the D.I. is zero. Resulting positive values

of the index can be interpreted as percent of minority overrepresentation

and negative values as percent of underrepresentation. These interpretations disregard sampling variability.

When a D.I. is calculated for a population or where all frequency

counts are large, any D.I. with an absolute value which is moderate or

large leads the researcher to reject the assumption that all factors are constant. However, when a D.I. is of small magnitude or at least one frequency is small or when an inference from a sample to a population is

made the researcher has to decide whether the assumption should be

rejected. If any nonzero D.I. value is taken as grounds for a decision

to reject the assumption, the researcher risks the expenditure of

resources studying a situation in which the assumption may be valid.

The pages to follow are intended to facilitate just such a decisionmaking

process in the hope of minimizing the misdirection of energy and resources.

An algebraically equivalent expression of the D.I. is produced by

considering the Actual Number of minority individuals who are observed.

in the category of interest in comparison to the Expected Number, which

is the proportion of the eligible population which is minority multipliedi

by the total number of persons selected for the category. Thus, the

Difference Indicator can be expressed:

D.I. Actual Number x 100 - 100 (2)

Expected Number

-2-

It
This form of indicator, computed from integers and incorporating an

explicit standard of comparison may be less mathematically elegant, but

is perhaps more easily comprehended. It may also help to clarify that a

D.I. value of zero is anticipated only when selection for inclusion in a

category is independent of group membership. Which formula is used for

computation is primarily a matter of convenience. Actually, each

requires the same information.

The D.I. can only measure the effects of institutional discrimination

upon minority group representation in the category. A single value can

provide no information regarding the causes of the results. Furthermore,

the magnitude of a D.I. is not affected by any discrimination factors

which temporally precede the delimitation of the eligible population.

For example, suppose that specifically due to past discriminatory hiring

practices in the Widget Corporation, there are very few women in junior

executive positions. When a D.I. is calculated for evaluation of

promotions of women to senior executive slots based upon junior executives

as the eligible group, any past influence upon the likelihood of women

filling the senior executive jobs is ignored. Thus, the D.I., in

general, will tend to underestimate the extent of past-in-present forms

of institutional discrimination.

The above example underscores the importance of the specific characteristics of the eligible population in influencing the value of the

D.I. Consider an additional D.I. using the same promotion situation,

however, based upon a less narrow group of eligibles. All female

employees in the company are counted among those eligible. To the

extent that a greater proportion of the total employees than of the junior executive population is female, the new D.I. will be more negative,

now reflecting past direct and indirect discriminatory practices toward

female employees. If there were current discrimination against women as

reflected by their diminutive numbers at all levels of the company, the

D.I. could only detect it if the eligible group were taken as applicants

or some other appropriately general population.

In a similar manner, a series of D.I.s for a given dimension can be

calculated for increasingly specific groups of eligibles. Whenever the

basis for refinement of the eligible group is correlated with the

probability of inclusion in the category, the magnitude of the D.I. will

be influenced. Continuing with the same example, if one of the rules

for promotion to senior executive were employment with the company for

20 or more years, a restricted eligible group might be defined as junior

executives having at least 20 years of employment. If in the redefined

eligible group proportionately more females than males were eliminated

from the eligible group, the new D.I. would be less negative than the

previous value. Furthermore, in general the variable thus controlled

-3-

op
for--time with the company in this case--would be identified as a

producing factor. Clearly, such a variable could be mediating for other

variables, including direct institutional discrimination, and should not

be simplistically interpreted as causative per se. Successive variables

can be controlled for in this manner. Any which produces no change in

the D.I. can be identified as extraneous to the category under study.

Thus, procedures are available for investigating variables which may or

may not be related to any specific situation.

In many applications of the D.I. the numbers used for calculation

of the required proportions are sufficiently small that it is advisable

to assess the magnitude of random variability upon the indicator. Two

specific problems in reliability frequently arise. The first concerns

the reliability of a single D.I. value. The second relates to the

reliability of differences among D.I.s. The problems can be phrased in

other words as a decision whether a numerically small D.I. value of

difference between two D.I.s should be judged as due merely to chance or

to other factors.

RELIABILITY OF DIFFERENCE INDICATOR VALUES

A method for testing whether a single D.I. is different than zero

when the relevant frequencies are large has been suggested by Nordlie

and Chosh. In this case w may be considered a parameter and P tested

against it. Under a null hypothesis that D.I. equals zero, confidence

intervals for the desired alpha level can be established based on:

SD = (100 lir(l -ir)/n)r, (3)

where n equals the number of minority individuals in the eligible

population. Use of this procedure is not recommended if any of the

frequency counts involved is less than 25.

Suppose a researcher at Wearout Products, which has 2,500 employees,

decides to investigate whether disproportionate numbers of minority

individuals have been laid off during a business slump. The relevant

parameters are observed as follows: w = 500/2500 = .20 (proportion of

employees who are minority group members), n - 250 (total number of

employees laid off), P = 80/250 - .32 (proportion of persons laid off

who are minority group members), and the alpha level is set at .05.

Calculation of the D.I. yields a value of 60. SD equals 12.65. Therefore,.

the critical region bounds are given by

±Zl-(al2)SS. (4)

-4-
For this example the bounds are -24.8 and 24.8. The obtained D.I.

lies outside. Thus, the researchers concludes the D.I. is not zero and

that some factor other than chance is operating in this situation.

Next, an attempt would be made to identify specific correlates with the

disparate situation, perhaps by calculating additional D.I. values based

upon modified eligible populations.

When the numbers involved in the calculation of a D.I. are not

extremely small the null hypothesis that D.I. = 0 can also be appropriately

tested using a chi-square test with one degree of freedom and Yate's

correction. If the values are extremely small, Fisher's exact test

could be used (Hays and Winkler, 1971). Figure I shows the numerical

values needed. The estimates of P and w are a/Ca + b) and (a + c)/N,

respectively. It can be seen that for any given situation where a D.I.

is calculated a 2 x 2 table can be constructed. Note, however, that

while any 2 x 2 table determines a unique D.I. value, the reverse is not

true.

Category Membership

yes no

Minority yes aa + b

Group

Member no cc + d

a+c b+d N

Figure I. Numerical values for calculating a difference indicator.

5

-- 5 -
Since calculations of chi-square statistics can be tedious and many

potential users of the D.I. may be discouraged by the necessity of such

endeavors, a short-cut method for testing index values was sought. The

Monte Carlo method seemed promising. A computer program was prepared

which systematically examined more than 2.0 x 104 selected 2 x 2

tables, calculating corrected chi-square values for each. Tables for

which the probability of a chance occurrence was less than .05 were more

carefully analyzed. An examination of "worst cases" revealed that the

set of distributions among the 2 x 2 tables significant at the .05 level

could be summarized by values derived from the tables without too severe

a power loss compared to the testing of individual tables. Figure 2

presents the results of the analysis, displaying D.I. values as a

function of the Expected Number of minority individuals, which in the

notation of Figure 1 is equivalent to (a + c)(a + b)/N. When the

Expected Number of minority individuals is less than six, Fisher's exact

test may be applied.

In the derivation of the function presented in Figure 2 it was

necessary to invoke several assumptions of which users should be cognizant.

The number of minority individuals in the total eligible population has

been assumed to be less than half of the total. Further, the selection

ratio, (a + c)/N, has been assumed not to exceed .25. If in a specific

case either of these circumstances does not hold, it is recommended that

the chi-square test be conducted rather than depending upon the values

in the figure.

RELIABILITY OF DIFFERENCE INDICATOR DIFFERENCES

The second problem arises as the situation where one wishes to compare

two D.I. values, seeking to determine whether they differ significantly.

This need arises when D.I.s from different time intervals are available

or when organizations are being compared. A computer study of the

variables comprising the ratio lead to the conclusion that direct

comparison of D.I. values involves several practical difficulties.

Identical D.I. values can reflect drastically different 2 x 2 tables,

and more seriously, very large D.I. differences can be produced which do

not reflect important differences between the respective underlying 2 x

2 tables. Hence, a test was developed based upon P, the proportion of

persons in the category of interest who are minority group members. The

basic procedure is as follows:

First, from the two Expected Numbers used to calculate the two

D.I. values being compared, select the smaller and call it the Minimum

Expected Number, MEN. Next, for each D.I. calculate the Minority

6

,I .
0> D 0 00 D 00 0 0 C

Lin

-1 0

*1 c

qc

c'cc

-M T

0 4

U. -j

4.1

O 0n 0 0 0 0 C\I 0 0 '-4 - I U

0 ...J -Z~ L&~ 

-7-E

'I, - -
Incidence Rate, MIR, which equals the Actual Number of minority individuals

in the category divided by the Total Number of individuals in the

category. Next, subtract the smaller MIR from the larger MIR to obtain

the difference between the values, HIRD. Finally, locate the value in

Table 1 which is nearest to the obtained MEN. If the MIRD is greater

than the value in the table, the difference in Ps underlying the D.I.

values is significant at the .05 level.

Table I

DIFFERENCE BETWEEN TWO DIFFERENCE INDICATOR VALUES

Minimum Expected Minority Incidence

Number Rate Difference

10 .20

20 .18

30 .16

40 .14

50 .12

75 .09

100 .07

The test is an approximation derived from the standard test between

two independent proportions. When samples may not be independent, as

would be the case when data from two time periods for the same organization

were being evaluated, a loss in power must be expected. Several additional

constraints were imposed in development of the test, and therefore must

be considered when using it. If the MEN value is less than 10, it is

recommended that the test not be used. In the development of the tabled

values it was assumed that the numbers of minority individuals in the

two eligible populations were within 20 percent of one another. It was

also assumed that minorities comprise less than 50 percent of each

eligible group. If either of these circumstances does not hold in a

specific instance, use of the test is inappropriate.

,'-. 8 - -
CONCLUSION

This paper has attempted to provide information about some of the

statistical properties of an indicator which can be used to measure and

assess changes in the manner in which an organization makes personnelrelated decisions. To assure that minorities are guaranteed equal

opportunity and treatment requires more than just good intentions on the

part of decisionmakers and managers. Rhetoric is also insufficient.

What is necessary is an examination of facts, and when unfairness is

found, an appropriate, timely modification of the relevant system

elements. The D.I. offers a succinct mode of description for such data.

It can be of value not only for detecting and investigation disparaties

between minority and majority personnel, but also for demonstrating the

absence of a difference when no difference exists. As is the case with

any statistical procedure, the user must not make blind application of

the tool. It is hoped that the research reported here will facilitate

the appropriate and meaningful use of the method to pursue the eradication

of institutional discrimination within a variety of organizations.

|I

• !o
REFERENCES

Feagin, J. R. Discrimination American style: Institutional racism and

sexism. Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1978.

Hays, W. L. and Winkler, R. L. Statistics: probability, inference,

and decision. N. Y.: Holt, Reinhart, & Winston, 1971.

Knowles, L. L. and Prewitt, K. Institutional racism in America.

Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1969.

Nordlie, P. G., Edmonds, W. S., and Goehring, D. J. Commanders'

handbook for assessing institutional discrimination in their

units. ARI Technical Report TR-78-B13, July 1978.

Nordlie, P. G., and Ghosh, D. N. Personal communication, November 1977.

Nordlie, P. C., Thomas, J. A., and Sevilla, E. R. Measuring changes

in institutional racial discrimination in the Army, DA PAM 600-43,

April 1977.

k

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I USA Arctic Test Ctr. APO Seattle. ATTN: STEAC-PL-MI 1 Senior Army Adv., USAFAGODITAC, Elgin AF Aux Fid No.09

1 USA Arctic Test Ctr. APO Seattle. ATTN: AMSTE-PL-IS 1 HO, USARPAC. OCSPE R, APO) SF 96668 ATTN: GPPE SE

I USA Armament Cmd. Redstone Arsenal. ATTN: ATSK-TEM I Stutteon Lift. Academy of Health Scimnces, Ft Sam Houtton

I USA Armament Cmd. Rock Island. ATTN: AMSAR-TDC I Marine Corps Int., ATTN: Dean-MCI

I FAA.NAFEC, Atlantic City. ATTN: Library I HO, USMC, Commandant. ATTN: Code MTMT

1 FAA-NAFEC, Atlantic City, ATTN: Human Engr Br I HO. USMC. Commandant, ATTN: Code MPI-20-20

I FAA Aeronautical Ctr. Oklahoma City, ATTN: AAC-440 2 USCG Aceaey New London. ATTN: Admission

2 USA FId Arty Sch. Ft Sill. ATTN: Library 2 USCG Aced",y New London. ATTN: Library

I USA Armor Sch. Ft Knox, ATTN: Library 1 USCG Training Ctt. NY, ATTN: CO

1 USA Armor Scfi. Ft Knox. ATTN: ATSB-OI-E I USCG Training Ctr. NY. ATTN: Educ Soc Ofe

I USA Armor Secs. Ft Knroxr, ATTN: AISODT TP 1 USCG, Psycliol Res Br, DC, ATTN! GP 1/62

1 USA Armor Sch. Ft K~nox, ATTN: ATSB-CO-AD 1 HO Mid-Range Br, MC ot, Ouantico. ATTN: PAS5 Div

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I US Marine Corps Liaison Ole, AMC. Alexandria, ATTN- AMCGS-F I Det &Civil Inst of Enviro, Medicine. Canou.

I USATRADOC, Ft Monroe. ATTNt ATRO-EO 1 AIR CRESS, Keeingson, ATTN: Info Sys Or

6 (JSATRADOC. Ft Monroe. ATTN: ATPR- AD I Milisaerptvikologisk Tianeste, Copenhasgin

I USATRADOC. Ft Monroe, ATTN: ATTS-EA 1 Military Attache, French Embassy. ATTN: DOC Sac

I USA Forces Cmd, Ft McPherson, ATTN: Library I Medecin Cheft, C.E.R.P.A.-Arerial Totnlon/Narul France

2 USA Aviation Test Sd. Ft Rucker, ATTN: STEBG-PO I Prin Scientific Off, Appl Hum Engi Rsch Div, Ministry

IULSA Agcy for Aviation Safety, F I Rucker, ATTN: Library of Detente, New Delhi

1 USA Aey for Aviation Safety, Ft Rucker, ATTN: Educ Advisor 1 Pers Rsch Ofc Library, AKA, Israel Defense Forces

I UISA Aviation Sch, Ft Rucker. ATTN: PO Drawer 0 1 Ministeris van Orafensle. OOOP/CL Afd Sociasl

1 HOUSA Aviation Syt Cmd, St Louis, ATTN: AMSAV-ZDR Psvchologischa Zalcen, The Haglue. Netherlands

2 USA Aviation Sys Test Act., Edwards AFB, ATTN: SAVTE-T

I USA Air Oef Scis, F, Bliss, ATTN: ATSA TEM

I USA Air Mirlmlity Rich & Dev Li), MoffettS Fld, ATTN: SAVDL -AS

I UISA Aviation Sth, Ret Trig Mgt, Ft Rucker, ATTN: ATST-T-RTM

1 USA Aviation Sch, CO. Ft Rucker, ATTN: ATST-D-A

1 HO, DARCOM, Alexandria. ATTN: AMXCO-TL

1 HO, DARCOM. Alexandria. ATTN: CDR

I US Military Academy, Wett Point, ATTN: Serials Unit

1 US Military Academy. Wet Point, ATT~N: Ole of Milt Ldrshp

t US Military Academy. West Point, ATTN: MAOR

IUSA Standardization GP. UK. FPO NY. ATTN: MASE -C

I Oft: of Navel Rsch. Arlington, ATTN: Code 452

3 Ole of Naval Rsch. Arlington. ATTN: Code 458

I Of c of Naval Rscfs, Arlington, ATTN: Code 450

I Ole of Naval Rschi, Arlington, ATTN : Code 441

1 Naval Aerospe Med Ret Lab, Pensacola, ATTN: Acout Sch Div

I Naval Airrostir. Med Res Lab. Pensacola, ATTN: Code 151

I Naval Aerospi: Med Res Lab, Pensacola, ATTN: Code LS

Chief of NavP#rs, ATTN: Pert-OR4

1 NAVAIRSTA, Norfolk, ATTN: Safety Ctr

1 Nav Ocaenographic, DC, ATTN: Code 6251, Charts & Tech

ICenter of Naval Anal. ATTN: Doc Ctr

1 NavAirSysCo, ATTN: AIR--5313C

I Nev SuMed, ATTN: 713

I NweHalkoptinSubSqua 2. FPO Sc 96601

I APHRL (FT) Williamts AFO

I AFHRL ITTI Lowry AFS

I APHRL 1AS) WPAF8, OH

2 APHRL (DOJZ) Brooks AFS

1 APHAL (DOJN) Lackland AFB

I HOIJSAF (INYSO)

I HOUISAF IDPXXA)

1 AFVTG (RDI Randolph AFB

3 AMAL (HE) WPAFS, OH

2 AF Inst of Tech, WPAFB. OH. ATTN: ENEISL

I ATC IXPTOI Randolph AFS

I USAF Aeroe Lih. Brooks AFB (SUL -4), ATTN: DOC SEC

1AFOSR INl). Arlington

1 AF Log Cmd, McClellain AFS. ATTN: ALCIDPCRS

1 Air Force Academy, CO. ATTN: Dept of Owl Sen C5 Navera & 0ev Cr, San Diego

2 Navy Mosl Neuropsyctiiatric Rsclt Unit. San Diego

1 Nav Electronic Lab, San Diego. ATTN: Res Lab

I Nav TroigCen, San Dlego. ATTN: Code 9000- Lib

1 NavPossGraSch. Monteiey, ATTN: Code 5SA@a

I NavPrjst~r#Sch. Monterey. ATTN: Code 2124

1 NavTrngEquipCtr, Orlando. ATTN! Tech Lib

I US Dept of Labor, DC. ATTN: Manpower Admin

1 US Dept of Justice. DC. ATTN: Drug Enforce Admin

1 Nat Sur of Standards. DC, ATTN: Computer Info Section

I Nat Clearing Howse for MH--lnlo, Rockville

1 Denver Federal Ctr. Lakewood, ATTN4: SIM

12 Defense Documentartion Cetste

4 Dir Psych, Army Hq. Russell Oces, Canberra

I Scientific Advar, Mil Sd. Army Hg. Russell 01cr. Canberra

I Mil and Air Attache, Austrian Embassy

I Centre dir Recherche Des Factaurs. Humaints do Is Defente

Nationales, Brussels

2 Canadian Joint Staff Washington

I C/Air Staff. Royal Canadian AF, ATTN: Pars Std Anal Sr

3 Chief, Canadian Def Rschi Staff. ATTN: C/CROS(WI

4 British Del Staff, British Embassy, Washington

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