Exhibits to Rebuttal to Draft Report (06!29!2012)

8/11/2019 Exhibits to Rebuttal to Draft Report (06!29!2012)

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Evaluation of Employment Outcomes by Ethnicity atTFK J/Vs Sound Transit Project

June 29 2012

222 S.W. Columbia St., Suite

1600

Portland, OR 97201

Phone: 503-222-6060

www.econw.com


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CONTACT INFORMATIONThis report was prepared by Dr. Bryce Ward of ECONorthwest, which is solelyresponsible for its content.

ECONorthwest specializes in economics, planning, and finance. Founded in 1974, wereone of the oldest independent economic consulting firms in the Pacific Northwest.ECONorthwest has extensive experience applying rigorous analytical methods toexamine the benefits, costs, and other economic effects of environmental and naturalresource topics for a diverse array of public and private clients throughout the UnitedStates and across the globe.

For more information about ECONorthwest, visit our website athttp://www.econw.com .

For more information about this report, please contact:

Bryce WardECONorthwest222 SW Columbia StreetPortland, OR 97201503-222-6060


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ECONorthwest The Economic Costs of Medical Errors in Oregon iii

TABLE OF CONTENTS

CONTACT INFORMATION .......................................................................................................I

TABLE OF CONTENTS .........................................................................................................III

I.BACKGROUND AND SUMMARY OF FINDINGS...................................................................... 1

II. DATA AND METHODS .................................................................................................... 3

A. Data .................................................................................................................................... 3

B. Methods .............................................................................................................................. 4

III. RESULTS ...................................................................................................................... 6

IV.EXPLANATION ............................................................................................................. 12

A. Comparison to Capitol Hill Site ......................................................................................... 12

B. TFK difficulties obtaining qualified laborers ..................................................................... 14

C. Evidence from applications and EEOC responses .......................................................... 15

D. Evidence from jobs employing same management in other locations ............................. 17

V. CONCLUSION .............................................................................................................. 20

APPENDIX ASELECTED APPLICATION AND INTERVIEW MATERIALS................................... 21


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ECONorthwest Evaluation of Employment Outcomes at TFK J/V 2

(3) Polissar and Neradileks analysis comparing TFKs outcomes to outcomes atdifferent Sound Transit project does not support meaningful conclusions

because it rests on faulty assumptions.Polissar and Neradilek compare TFKsemployment outcomes to outcomes from a similar Sound Transit project (CapitolHill); however, for this analysis to prove useful, one must assume that both sitesdrew workers from the same labor pool, to do the same work, using a randomprocess. These assumptions are invalid, and, as such, this analysis does notprovide useful information.

(4) Polissar and Neradilek do not investigate the possibility that differences inoutcomes across ethnic groups reflect differences in the qualifications and

skills among those dispatched.As Polissar and Neradilek state in their report,the only potentially causative factor studied is ethnicity. Qualifications andother factors were not considered. Clearly, though, qualifications and otherfactors matter. An analysis of information contained in a mix of employmentapplications, interview notes, and resumes for a subset of the laborers dispatchedto TFK indicates that the laborers who were turned around or dismissed due toinability to perform were substantially less likely to provide clear evidence of

prior experience on large tunneling projects than laborers who were hired andnot dismissed for reasons related to job performance. While the informationrelied upon in this analysis does not include all TFK laborers and may notprovide a complete and accurate description of the qualifications for theindividuals examined, this analysis certainly suggests that differences inqualifications were important. As such, to assert that the observed disparities arethe result of discrimination requires one make the baseless assumption that nodifferences in qualifications or other relevant factors exist across the relevantindividuals.

In the remainder of this report, we describe the results of our analysis and each of thesekey findings in more detail. We find that statistically significant disparities in outcomesbetween African Americans and other ethnic groups are limited to a subset ofoccupations within a single union laborers group 6 or higher (i.e., tunnel miners).Quantitative and qualitative evidence indicates that TFK had significant difficultiesfinding qualified workers in these groups, regardless of ethnicity, and that the tunnelminers dismissed were dismissed for reasons related to performance or qualification.This supports TFKs assertion that worker qualifications explain observed differences inoutcomes. We also demonstrate that, at previous jobs in other cities that employed thesame TFK supervisory team, African American outcomes do not statistically differ fromoutcomes for other ethnic groups. This also supports TFKs assertion that workerqualifications explain observed differences in outcomes. Combined, these facts suggest

that it is plausible that unobserved differences in worker qualifications explain theobserved differences; however, without more complete data on the qualifications andabilities of the workers at issue, we cannot definitively explain the observed pattern ofresults.


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II. DATA AND METHODSStatistical analyses of employment outcomes typically address three main questions:

(1)Do we observe meaningful differences in outcomes across groups?(2)Do observed differences stem from group status? That is, does group status

cause differences in outcomes because group members face discrimination or dodifferences across groups stem from other, potentially unobserved, factors likequalifications or experience that may be correlated with group status? Stated inthe language of statistics, are estimated differences inaccurate or biased?

(3) Assuming observed differences are unbiased, are observed differences likely dueto chance (i.e., are differences statistically significant)?

A. Data

To the extent possible, we address these questions using data provided to us by TFKrepresentatives. Specifically, we examine data that includes the following:

Ethnicity

Union Membership

Worker classification (as identified on dispatch slip)

Dispatch date

Total hours worked

Separation date (if any)

Reason for termination3

In the analyses described below, we rely on the information we were provided specifically, the data in the most recent file we were provided -- Graphs as of

52912.xlsb; however, we also examined the data used by Polissar and Neradilek.4 Aswe understand it, all datasets ultimately rely on data maintained by Sound Transit.5

It is very important to note that the data available contain several significant potentially fatal flaws. The data examined by Polissar and Neradilek do not match thedata we examined. While we do not understand the source of these differences at thistime, the differences we observe are very troubling.

First, the list of people named in the different datasets are not identical. Setting aside thedozens of individuals whose names have slight differences in spelling across the datasets (which weve assumed are typos and not separate individuals), the data we receivedincludes seven individuals who are not included in the Polissar and Neradilek data even though their orientation dates indicate they were dispatched during the period

3 Specifically, use files provided by TFK labeled Graphs as of 52912.xlsb (specifically the data in the inputgraphs tab), TFKJV Weekly Employee hours for 2010 & 2011.xlsx, and U220-W.xisx.

4 The files we reviewed from Polissar and Neradilek were labeled U220 04 05 12 Analysis Hiring andTermination Data Revised.xls and U230 03 19 12 Analysis Hiring and Termination Data Revised.xls

5 Information from Jeremy Saperia


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covered by the Polissar and Neradilek data. Similarly, the data examined by Polissarand Neradilek include five individuals whose names are not included in the data wereceived. As such, 8 percent of the total number of laborers across both datasets are notincluded in one data set or the other.

Second, among the 137 laborers in both data sets, 13 (or nearly 10% of the total numberof observations) have a different ethnicity code. For instance, 2 individuals are coded asAfrican American in the data set we received, but are coded as Caucasian in the Polissarand Neradilek data, and one individual coded as Caucasian in our data is coded asAfrican American in their data.6

Third, dispatch/orientation dates, termination dates, and hours worked differ forseveral individuals in both data sets. For instance, 8 individuals havedispatch/orientation dates that differ by more than two weeks across both data sets.Two individuals show up as terminated in the Polissar and Neradilek data, but notterminated in our data, and two different individuals have termination dates more than100 days apart between the two data sets. Finally, total hours worked are inconsistent

across data sets.7

In particular, hours differ by relatively significant amounts for mostindividuals who worked hours in 2011.

The existence of such differences across data intended to describe the outcomes for thesame set of individuals cast doubt on the reliability of any statistical analysis based onthese data. Given the relatively small number of individuals included, data errorsreflecting relatively few individuals could significantly affect the magnitude of observeddifferences and the statistical significance (or the reliability) of the results. Until thesedata issues can be satisfactorily resolved, any statistical analysis should be interpretedwith extreme caution.

B. Methods

Setting aside concerns about the reliability of the data, our statistical analyses rely onmethods similar to those used by Polissar and Neradilek. Because TFKs project isongoing, we have not observed final outcomes for each worker. Thus we cannotcompare final outcomes for all workers because we have not observed them.Statisticians refer to such data as censored, and they use a particular form of statisticalanalysis known as survival analysis (also know as time to event or duration analysis)when examining such data.8

6 Even within a single excel file, some individuals have multiple ethnicities, names, etc. For instance, theU220-W.xis file contains tabs for which describe hours worked per week for each worker in each year, 2

individuals change ethnicity code across years, a few change name spelling, etc.. This data set also has sixindividuals who are listed as laborers in the Polissar and Neradilek data and in Graphs as of 52912.xlsb,listed as operators.

7 This description compares the Polissar and Neradilek hours to the hours reported in TFKJV WeeklyEmployee hours for 2010 & 2011.xlsx

8 For additional details regarding survival analysis see UCLA Academic Technology Services, StatisticalConsulting Group Survival Analysis with Statahttp://www.ats.ucla.edu/stat/stata/seminars/stata_survival/default.htm(accessed May 21, 2012),Kennedy, P., 2008.A Guide to Econometrics 6E.Malden, MA: Blackwell Publishing.


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Unfortunately, though, one cannot reliably address the fundamental question of interestusing the available data. We do not have complete, reliable data on individualqualifications or skills. We only have information gleaned from a mix of employmentapplications, interview notes, and resumes for a subset of TFK workers. As such, we canonly partially assess question (2) do observed differences reflect group status or dothey reflect other attributes that may be correlated with group status in the data (i.e.,qualifications and skills). We cannot definitively explain the source of any observeddifferences. To assert that observed differences reflect discrimination, one must assumethat no differences exist in qualifications or skills across groups in the sample of individuals weactually observe.We are aware of no evidence that would support such an assumption,and the evidence available appears to directly contradict it.


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III. RESULTSBefore describing outcomes by ethnic group, we examine some general descriptive factsabout TFK workers. Table 1 presents some general facts about employment outcomes foreach union. In this table and many of the others in this section, we present raw counts

(as opposed to percentages). We do this to make very clear the relatively small samplesizes that underlie this analysis.

Through May 25, 2012, 282 workers had been dispatched to the TFK project.Approximately 57 percent came from the laborers union, another 26 percent came fromthe operators union, and the remainder were split between the carpenters and thecement masons unions. A small number of people (16 mostly laborers) were dispatchedon two separate occasions.9Thus, 264 different individuals were dispatched to the TFKsite. The median job tenure is longest for operators (394 days) and shortest for carpenters(93 days) and laborers (188 days). In part, the brevity of laborers tenure reflects theirlater median start date.

Table 1. General Facts About Employment Outcomes for Each Union

Number ofdispatches

Number

dispatchedindividuals

Number

dispatched 2

separatetimes

Median

number ofdays on job

Medianstart date

Carpenters 34 33 1 93 19-Nov-10

CementMasons

12 10 2 260 13-Jul-10

Laborers 160 149 11 188 20-Jun-11

Operators 74 72 2 394 18-Mar-11Total 280 264 16 222 11-Apr-11

Source: ECONorthwest analysis of data provided by TFK

Table 2 describes the ethnic composition of workers dispatched from each union. Of theminorities dispatched to TFK, most (75%) came from the laborers union.

9 Some of these reflect people laid-off after temporary work ended who were called back. Some representpeople who were turnaround that were dispatched again. For instance, TFK turned around some laborerswho were qualified for cross-path work, but not for the tunnel boring machine (TBM) work for which theywere hiring. Email from Michael Krulc June 27, 2012.


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Table 2. Ethnic Composition of Workers Dispatched from Each Union

Carpenter Cementmason

Laborer Operators Total

African American 1 1 29 3 34

Asian 2 0 2 0 4

Caucasian 25 4 68 59 156

Hawaiian/Pacific Isla 0 1 0 1 2

Hispanic 1 2 31 3 37

Native American 1 1 5 2 9

Other 3 1 14 4 22

Total 33 10 149 72 264


TFK data describe the reason for each job separation. Separations are grouped into oneof seven categories: accepted other work, medical reasons, end of temporarywork/reduction in force, failed to report/absences, falsification/nodispatch/insubordination/violation of safety rules, inability to perform, and turnaround.Table 3 describes the reason workers left TFK by union.

Table 3. Reason Workers Left TFK, by Union

Carpenter Cement

Mason

Laborer Operators Total

Accepted Other Work 2 0 6 7 15

Medical 0 0 4 0 4

End Temp Work / Reduction of

Force

26 9 17 10 62

Failed To Report, absences 1 0 3 1 5

Falsification; No Dispatch;

Insubordination; violation safetyrules

1 0 4 3 8

Inability to Perform 1 0 17 1 19

Turnaround 0 0 19 0 19

Total 31 9 70 22 132


There are clear differences across unions in the reasons for departure. One hundredpercent of the 19 workers who were turned around came from the laborers union.


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Table 4. Reasons for Separation, by Ethnicity and Union

AfricanAmerica

n

Asian Caucasian Hawaiian/

Hispanic NativeAmerica

n

Other Total

Non-Laborer Unions

Accepted Other Work 0 0 9 0 0 0 0 9

Medical 0 0 0 0 0 0 0 0

End Temp Work /

Reduction of Force

2 2 33 2 3 1 2 45

Failed To Report,

absences

0 0 2 0 0 0 0 2


Insubordination; violationsafety rules

0 0 3 0 0 1 0 4

Inability to Perform 1 0 1 0 0 0 0 2

Turnaround 0 0 0 0 0 0 0 0

Total Non-Laborer Unions 3 2 48 2 3 2 2 62

Laborers

Accepted Other Work 1 0 4 0 0 1 0 6

Medical 3 0 1 0 0 0 0 4

End Temp Work /

Reduction of Force

4 0 7 0 5 1 0 17

Failed To Report,

absences

1 0 2 0 0 0 0 3


Insubordination; violationsafety rules

0 0 1 0 2 0 1 4

Inability to Perform 6 0 7 0 2 0 2 17

Turnaround 6 0 5 0 6 0 2 19

Total Laborers 21 0 27 0 15 2 5 70


The bottom panel of Table 4 presents the outcomes for the laborers union broken downby ethnicity. For each of the large ethnic groups (African Americans, Caucasians, andHispanics) from the laborers union, a large share of people who cease work at TFK wereeither turned around or dismissed due to inability to perform. Of the 21 AfricanAmericans who left work at the TFK site, 6 were turnarounds and 6 were dismissed forinability to perform. Of the 27 Caucasians who left the TFK site, 5 were turnarounds and7 were dismissed due to inability to perform. Of the 15 Hispanics who left the TFK site, 6were turnarounds and 2 were dismissed due to inability to perform.

While each of the major ethnic groups experienced a significant number of separations including a significant number of turnarounds and dismissals for inability to perform,African Americans experienced a disproportionate share of separations. Consistent withthe findings in Polissar and Neradilek, the differences between African Americans and


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the other ethnic groups within the laborers union are greater than we would expect dueto chance alone. The results from a survival analysis similar to the one described abovefor the non-laborer unions indicate that, if African Americans and Caucasiansexperienced separations at the same rate, we would expect to observe 11.53 separationsfor African Americans and 36.47 separations for Caucasians. In actuality, we observe 21separations for African Americans and 27 separations for Caucasians. These differencesare statistically significant (p-value


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among apprentices are small and not close to statistically significant at the commonlyused 0.05 percent level. Thus, the statistical significance in adverse employmentoutcomes for African Americans appears exclusively in the group 6 subset of a subsetof workers.13

Table 6. Results of Survival Analysis by Laborer Worker Group

Apprentice Group 3 & 4 Group 5 Group6+

Expected Events

African Americans

3.98 4.3 1.32 4.42

Actual Events African Americans

4 4 3 10

Expected Events --

Caucasians

2.02 4.7 12.68 14.58

Actual Events --

Caucasians

2 5 11 9

P-value 0.99 0.84 0.12 0.001

Source: ECONorthwest log-rank test of data provided by TFK

In sum, the simple analyses described above indicate: (a) relative to Caucasians (andother ethnic groups), African Americans are more likely to have experienced anyseparation or a separation related to individual performance and (b) differences inAfrican Americans employment outcomes are not ubiquitous instead, they areconcentrated within a single union (laborers) and within specific job classificationswithin that union (TW group 6 and, to a lesser extent, group 5).

Polissar and Neradilek describe (a) but they do not describe (b), and (b) is important. Aconcentrated disparity indicates that the cause of the disparity is not common to theentire TFK project. Rather, the source of the disparity is concentrated in the parts of theproject that rely on group 6+ (and perhaps group 5) laborers.

13 Different combinations of groups do not change this fundamental finding. E.g., grouping apprenticeswith group 3 and 4 does not yield large or statistically significant differences. Similarly, grouping laborersapprentices with groups 3 and 4, and with all non-laborers does not yield statistically significant differences.Even an analysis that included every one but group 6+ miners does not yield differences that are statisticallysignificant at the commonly used 0.05 level.


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IV. EXPLANATIONThe results described above indicate that, for a particular subset of a subset of workers(group5/6 miners from the laborers union), a disparity exists between AfricanAmerican outcomes and Caucasian outcomes. However, as described in section III.A

above, due to uncertainty about the quality of the raw data, we cannot be certain thatthis statistical disparity is real. Furthermore, even if the pattern of results above isaccurate, these raw statistics do not explain the observed pattern. In the absence ofexplanation, we cannot interpret these differences. In this section, we investigatepotential explanations for the observed results using the limited data available to us.

As we understand it, the sides in this matter offer two competing explanations for theobserved differences. One side, the dismissed employees, argues that the patterndescribed above indicates discrimination by TFK against African Americans. The otherside, TFK, argues that the pattern reflects larger problems they had with the quality ofgroup 5/6 workers dispatched by the laborers union and that the dispatched AfricanAmericans happened to be disproportionately unqualified in that subset.

To distinguish among these competing stories we would ideally obtain extensive dataon each dispatched workers qualifications and abilities to perform the work required onthis specific project. For instance, we would like data that described each workersexperience with the tasks required in tunnel mining, their experience workingunderground, and performance evaluations from previous jobs that describe work ethic,attitude, etc. We do not have these data (we only have partial information obtained fromemployment applications, interview notes, and resumes for a subset of TFK workers).14As such, we cannot directly distinguish among the competing stories by evaluating theoutcomes of similarly qualified workers of different ethnicities (e.g., through amultivariate regression or some other form of multi-variable analysis).

A. Comparison to Capitol Hill Site

Polissar and Neradilek attempt to partially get around this limitation by comparing theemployment outcomes at TFKs University of Washington (UW) site to the outcomes atthe Capitol Hill (CH) site where Jay Dee/Coluccio/Michels Joint Venture (JCM) is thecontractor. They include this comparison because the CH site draws workers from thesame union hall as the UW site, and, according to Sound Transit staff, the work is similarfor the relevant employees, but there is a different contractor. 15This approach allowsone to distinguish among the competing stories if one assumes that both sites drewworkers from the same labor pool, to do the same work, using a random process. Underthese assumptions, the quality of workers dispatched to each site for each ethnic group

should be the same.16

As such, given a sufficiently large sample, the implicit theory

14 We describe the available information and analyze it in more detail below.

15 Polissar and Neradilek p.2

16 Technically, the underlying distribution of quality (e.g., the average quality) should be the same for alethnic groups, given a sufficiently large sample.


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appears to be that any differences between worker outcomes at the two sites reflectdifferences in the contractor and not differences in the quality of workers dispatched.17

While Polissar and Neradilek find that African Americans have a poorer workexperience at the UW site, the assumptions outlined above are not valid. As such, it isincorrect to conclude, based on this analysis, that contractor differences (e.g.,discrimination) explain the observed pattern. To their credit, Polissar and Neradilekexplicitly draw no such conclusions in their report.

Comparing the UW site to the CH site does not support meaningful conclusions forseveral reasons. First, as we understand it, the process via which workers are matched tojobs is not random. Contractors have the ability to give preference to workers they haveworked with previously (rehires) and call out specific workers by name. One of the jointventure partners comprising JCM, Coluccio, is local, but TFK is not (nor are Traylor orFrontier-Kemper). As such, JCM have much more knowledge about the local labor pooland potentially were able to select a greater percentage of their workforce directly.

Second, as we understand it, while the CH and UW jobs are similar, they are notidentical. The UW job is much larger. Through the periods examined in the Polissar andNeradilek report, the UW job had employed more than twice as many laborers as theCH job. The UW job is also more challenging. For example, the pressures to whichtunnel workers could be exposed exceeded 5 bar. In contrast, pressures on the CH jobonly reached 1.7 bar.18Higher pressures meant that TFK required more workers withspecialized experience and training.

The data clearly suggest that these (and perhaps other) differences matter. Workeroutcomes differ across sites for all ethnicities, not just African Americans. For instance,zero workers were turned around at the CH site. No African Americans. No Caucasians.No Hispanics. In contrast, 19 workers were turned around at the UW site, including 6

African Americans, 5 Caucasians, and 6 Hispanics.

Similarly, very few workers appear to have been dismissed for inability to perform afteronly a short period on the job at the CH site. While we do not have data that describe thereason for separation at the CH site, at the UW site 15 of the 17 laborers dismissed forinability to perform were dismissed within 40 days. This suggests that TFK put somemarginal laborers on the job and dismissed them relatively quickly once their qualitywas revealed.19In total, 69 percent of all laborer separations at the UW site occurredwithin 40 days of orientation. In contrast, only 5 out of 16 (or 31 percent) of separationsoccurred within 40 days of dispatch at the CH site.20

17 We note that Polissar and Neradilek do not state this logic explicitly.

18 Interview with Michael Krulc, April 25, 2012.

19 See various TFK EEOC responses to request for information for EEOC Charge No. #551-2011-01391, EEOCCharge No. #551-2011-00415 Amended, EEOC Charge No. #846-2012-10533, EEOC Charge No. #551-2011-01373

20 Expanding the period to 70 days or shortening to 30 does not eliminate the disparity.


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The disparities between the UW and CH sites, even among Caucasians, suggests thateither TFK received less qualified workers from the union hall (perhaps because itlacked the local advantage described above), TFK set higher standards for their workers(perhaps due to the challenges on this job described above), or both.

B. TFK difficulties obtaining qualified laborersRegardless of the specific reason for the difference between the UW and CH sites, thedata strongly support TFK's repeated claim that they struggled to find qualified miners(laborers in groups 5 and higher). As noted in section IV, TFK turned around ordismissed a substantial share of the workers dispatched by the laborers union and thevast majority of turnarounds and separations due to the inability to perform wereamong laborers in groups 5 and higher.

TFK's difficulties obtaining miners who met their standards are well documented. Wereceived several letters, emails, and other documents that describe TFK'sstruggles.21 TFK in various responses to EEO complaints, summarizes the problems

they faced:

Starting in the fourth quarter of 2010, and continuing thereafter, TFK beganrequesting [the] Union, Local 440, to provide miners to the Project site. TFKbelieved that the term miner was a term of art, generally recognized in theconstruction industry and by labor unions. Apparently, however, Local 440 did notshare TFKs definition of the term miner. When Local 440 did not dispatch thecaliber of miners TFK needed on the Project, the Joint Venture began identifyingfor Local 440 the characteristics of the miners TFK needed. Although the minersTFK needed to work on the Project in June, 2011 generally fell into the category ofGroup V/Group VI miners, Local 440 continued to dispatch an alarming number ofunqualified Group V Miners in response to TFKs requests for qualified miners who

possessed certain skills. TFK, therefore, was forced to implement an interviewprocess to determine whether the individual(s) Local 440 dispatched as GroupV/Group VI miners possessed the requisite skill set TFK needed its workers topossess to work on the Project. Once a dispatched miner arrived at the TFK Office,TFKs Site Superintendent, Bert Dore, conducted an interview with the prospectiveemployee.22

In the process of obtaining qualified workers, TFK took several extraordinary steps allof which underscore the serious problem they faced. They put out a call to the national

21 See footnote 11, Krulc, Michael A. Letter to Alan Clune, Laborers' Local 440, Seattle, WA. 19 Sep. 2011;Krulc, Michael A. Letter to Edwin F. Shorey, Seattle Tunnel and Rail Team (START), JV, Seattle, WA. 5 Jan.2012.; Krulc, Michael A. Letter to Edwin F. Shorey, Seattle Tunnel and Rail Team (START), JV, Seattle, WA. 9

Jan. 2012.; Krulc, Michael A. Letter to Edwin F. Shorey, Seattle Tunnel and Rail Team (START), JV, Seattle,WA. 2 Feb. 2012.; Krulc, Michael A. Letter to Alan Clune, Laborers Local 440, Seattle, WA. 22 Mar. 2011.;Saperia, Jeremy. Sound Transit Project Seattle, WA. E-mail to Sergio Rascon. 6 Jan. 2012.; Saperia, Jeremy.FW: Helmets to Hardhats Termination. E-mail to Anne Braudis. 18 May. 2012.

22 TFK J/V response to request for information EEOC Charge No. #551-2011-01373


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To help make this description more concrete, Appendix A contains application materialsfor a few selected individuals.27 Employee A, an African-American laborer, illustratesthe type of applicant who is nearly always successful at obtaining a job and keeping it.Employee A provides a complete resume with detailed description of his priorexperience, including work on two previous tunnel projects. He also checks nearlyevery box on the TFK certification and skill/experience checklist. Employee B, aCaucasian laborer, illustrates the type of applicant who is frequently turned around.The information we have for Employee B does not include an employment applicationor resume. We only have the TFK certification and skill/experience checklist, and, onthis form, Employee B indicates that he possesses only two certifications and only 10 outof 23 skill/experience requirement. Employee C, a Hispanic laborer, provides anotherclear example of the type of worker who was turned around. Again, for Employee C weonly have the certification and skills/experience checklist, and he possess three relevantcertifications and only 3 out of 23 skill/experience requirement. Finally, Employee D, anAfrican-American laborer, illustrates the type of worker dismissed due to inability toperform. Employee Ds information includes an application and two certification andskill/experience checklists. The employment application includes cryptic information

on work experience, and his certification and skills/experience checklist indicatesexperience with 14 out of 23 categories. His records indicate he may have someexperience, but the extent of his experience is unclear.

The second type of qualitative materials that suggest that qualifications and experiencematter are TFKs responses to EEOC complaints. These responses detail TFKs reasonsfor dismissing several employees, and these descriptions clearly indicate TFKs positionthat work performance was the reason for workers dismissal. We describe fourexamples obtained from these documents below. First, Employee E, an African-American Laborer, was dismissed due to inability to perform. Specifically, he wasdismissed because he could not perform basic mining tasks and appeared unable tofollow directions related to his own safety in the tunnel.28 TFKs response further

documents Employee Es failure to complete simple tasks correctly and his violation of aworkplace order relating to no foot traffic in the tunnel. Second, TFKs response to acomplaint by Employee F, an African-American laborer, documents complaints byEmployee Fs co-workers regarding his work effort and competency that werecorroborated by the observations of Employee Fs supervisor who noted two separateoccasions where Employee F took inordinate amounts of time recovering his tool beltfrom different locations.29 Third, TFKs response to the complaint of Employee G, anAfrican-American laborer, documents that Employee G engaged in several unsafepractices the led a co-worker to describe him as an accident waiting to happen, that hefailed to adequately complete assigned tasks (which led to co-workers having to re-dohis work), and that he twice neglected to warn co-workers of approaching locomotive

traffic.30

Finally, TFKs response to Employee H documents that TFK gave Employee H

27 We redact specific names and personal identifying information for confidentiality purposes.

28 TFK response to Request for Information, EEOC Charge No. #551-2011-01391

29 TFK response to Request for Information, EEOC Charge No. #551-2011-00415 Amended

30 TFK response to Request for Response, EEOC Charge No. #846-2012-10533


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repeated warnings about not pulling his weight. He was even moved between crewsin an effort to find a way to get him on the right track; however, ultimately, it wasconcluded that Employee H demonstrated not only a poor work ethic, which wasundermining crew morale, but [he was] also a safety hazard.31

Combined, the evidence from employment applications and EEOC responses clearlysuggests that worker qualifications and performance matter. Workers whose recordsclearly demonstrate prior experience tend to be hired and remain employed, while thosewhose records do not clearly indicate prior experience are more likely to be turnedaround. Furthermore, TFK records clearly describe several cases where job performance,not race, led to workers being dismissed due to inability to perform after a relativelyshort time on the job.

While we do not have the complete data on individual qualifications and performancerequired to statistically test the hypothesis that differences in qualifications andperformance explain the observed differences in worker outcomes, the information wehave reviewed is consistent with the view that qualifications and performance matter

and that they explain any observed differences.

D. Evidence from jobs employing same management in

other locations

While we do not have a complete data for the all of the individuals at issue in this matter,we do have additional data about the sponsoring contractor Traylor. As weunderstand, a substantial proportion of the supervisory team for the TFK job workedtogether for previous Traylor joint ventures.32 This allows us to conduct an analysis thatflips the logic of the Polissar and Neradilek UW vs CH analysis. Instead of comparingthe outcomes for different contractors drawing workers from the same union, weexamine the experience of the same contractor drawing workers from unions in adifferent cities. If we assume (a) the distribution of skills for the relevant workers differsacross cities and (b) that a contractor who discriminates would do so consistently acrossjobs, then this analysis can help us distinguish among the competing stories for theobserved differences in outcomes described above. If we do not observe differencesbetween African American and other ethnic groups outcomes in other locations, than itis more plausible that the differences we observe in Seattle reflect differences in abilitiesand not discrimination.

Specifically, we obtained data from two jobs completed in Los Angeles (the LA jobs) thatemployed the Traylor supervisory team currently working at the UW site theNortheast Interceptor Sewer Tunnel (the NEIS job) and the Metro Goldline Eastside

Extension for LA Metro (the MTA job).33 The data we were provided include ethnicity,

31 TFK response to Request for Information, EEOC Charge No. #551-2011-01373

32 Interview with Michael Krulc, April 25, 2012; email from Anne Braudis May 8, 2012

33 As we understand it several of the TFK management team also worked on these projects including TFKsuperintendent Bert Dore. Interview with Michael Krulc, April 25, 2012; email from Anne Braudis May 8,2012


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job classification and title (including union membership), hire date, rehire date, finaltermination date, and total hours worked for each job.34 Since the two jobs were largely(though not exactly) sequential, many people who worked on one job also worked onthe other. For instance, nearly one third of laborers in the data worked on both jobs. Inorder to avoid difficulties related to people hired briefly on one job and subsequentlytransferred to another and difficulties related to uncertainty about the precise durationsof employment, we combine the two datasets and examine total hours worked on bothjobs as our primary outcome of interest.35

Overall, worker outcomes on the LA jobs differ substantially from the outcomesobserved in Seattle. First, zero workers were turned around at the LA jobs.36Second,relatively few workers appear to have been terminated due to their inability to perform.As noted previously, approximately 30 percent of laborers dispatched in Seattle wereturned around or terminated for reasons related to individual performance, and the vastmajority of these terminations occurred within 40 days of orientation. In total,approximately one-third of dispatched laborers in Seattle worked fewer than 200 hoursthrough 2011. In stark contrast, in LA, only 11 percent of laborers worked fewer than 200

total hours. These facts further corroborate TFKs claim that they faced great andunusual difficulties obtaining qualified laborers in Seattle, and these facts providesupport for one of the key assumptions underlying this analysis that the distribution ofskills and qualifications among the dispatched workers from the relevant unions differacross cities.

Examining differences across ethnic groups, we do not find evidence that AfricanAmericans experienced worse outcomes than other ethnic groups at the LA jobs. Table 7presents average total hours37, percentage working fewer than 200 hours, and share ofNEIS workers retained for the MTA job by ethnic group for laborers. Relative toCaucasians, African Americans work more total hours, were less likely to work fewerthan 200 hours, and were more likely to move from the NEIS job to the MTA job. None

of these differences though are statistically significant at the commonly used 0.05 level.In fact, the differences in average hours and share working fewer than 200 hours havevery large confidence intervals (or very high p-values). This stems from both the smalldifferences in values and the relatively small numbers of African Americans in the data.Only 10 African American laborers were dispatched for these jobs.

While the small sample of African Americans limits our ability to draw strongconclusions from these data, the patterns we do observe do not suggest that the commonTraylor supervisory team discriminated against African Americans over the past decade.

34 The data for these analyses come from Traylor Brothers payroll system and were forwarded toECONorthwest on May 8, 2012.

35 We also do not have the date for all terminations we observe when people are rehired, but we do notobserve their original termination date (only their final termination date).

36 This finding from the data was confirmed by Jeremy Saperia.

37 We limit the sample in the total hours analysis to workers hired on date equal to or later than the firstAfrican American.


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Table 7. Summary statistics for LA jobs by Ethnicity

Average Total Hours Percent working


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V. CONCLUSIONIn sum, the data available do not support a conclusion that TFK discriminates againstminorities, particularly African Americans. The data produced by Sound Transitcontain numerous inconsistencies which may affect the accuracy and reliability of any

data analysis, particularly an analysis that includes relatively few data points. Settingaside the data issues, data analysis reveals that statistically significant discrepancies inworker outcomes are limited to one worker classification from a single union Group 6tunnel miners from the laborers union.38 Statistical analysis also suggests that atprevious jobs in a different city that employed an overlapping supervisory team, AfricanAmericans did not experience worse outcomes than Caucasians. Thus, to assume thatthis evidence indicates discrimination by TFK one must believe:

(1) The underlying distribution of qualifications and skills was the same acrossethnic groups for individuals dispatched to the TFK site (even though we areaware of no evidence that support this assumption and the limited availableevidence contradicts it)

(2) That the source of the discrimination only works with or discriminates againstAfrican Americans who are laborers in group 6 (or possibly 5) and higher

(3) That the source of discrimination is unique to the Seattle project (or was notpresent during the LA projects).

While we cannot rule out the possibility that all three of these beliefs may be true, thisappears implausible. Given that the affected subset of a subset of workers was preciselythe group with which TFK experienced significant difficulties finding qualifiedindividuals, it seems more plausible that the observed statistical discrepancy reflectsunobserved differences in individual ability, rather than racial discrimination.

38Differences between African Americans and Caucasians in group 5 may be significant if one expands thethreshold to determine statistical significance beyond the commonly used 0.05 level.


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APPENDIX ASELECTED APPLICATION AND INTERVIEW

MATERIALS


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Employee A


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Employee A


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Employee A


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Employee C


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Employee D


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Employee D


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Documents

Exhibits to Rebuttal to Draft Report (06!29!2012)