In the Crime Lab
Wendy S. Becker*
University at Albany
*Special thanks to Clif Boutelle, W. Mark Dale, James Farr, Mary Doherty, Frank Landy,
and Joel Philo for comments on earlier versions of this manuscript.
The field of forensic sciences has grown tremendously in the last decade. The transition from craft-based, labor-intensive work to automated, mobile systems makes for a fascinating study of work transformation. This growth has not come without attendant problems, especially in the nations crime labsproblems that can be solved with the assistance of industrial-organizational psychology. I-O can have a major impact on the field in areas such as performance measurement and the development and retention of forensic lab professionals.
Shared History
Forensic science is the study and practice of the application of science to the purposes of the law (Lucas, 1989). Technical specialties include pathology/biology, physical anthropology, questioned documents, toxicology, criminalistics, engineering, jurisprudence, odontology, general (which includes several smaller subdisciplines), psychiatry and the behavioral sciences. These 10 sections make up the American Academy of Forensic Sciences (AAFS), a nonprofit, professional society with 6,000 members
(http://www.aafs.org/). Like our own Division 14, AAFS was organized during the postwar explosion of interest in the sciences. AAFS sponsors an annual conference and publishes the
Journal of Forensic Sciences.
Interestingly, the forensic sciences and I-O psychology have common ancestors with links to shared history. For example, Francis Galtons 1892 book
Finger Prints provided the first scientific method for using fingerprints to solve crimes. Galton expanded his extensive collection by asking friends at parties to contribute prints. The basic approach, Galtons Details, is still in use today and
Finger Prints was reissued in 1965. Galtons research on facial features would foreshadow the first police identification kit.
Hugo Mnsterberg developed one of the first lie detectors when he administered a battery of psychological tests at the 1907 trial of Harry Orchard, a self-confessed mass murderer, being tried for the murder of the ex-governor of Idaho. Mnsterberg concluded that Orchard was innocent (Landy, 1992). Eyewitness accuracy, false confessions, and the prevention of crime were themes included in Mnsterbergs behavioral research agenda at Harvard and the 1908 publication, On the Witness Stand. Mnsterbergs work served as a forerunner to the field of forensic psychology in the United States (Spillman &
Spillman, 1993).
As applied sciences, both I-O and the forensic sciences have followed a similar trajectory concerning scientific legitimacy and limitations of professional scope with respect to the court system.
Frye v. United States ruled polygraph tests inadmissible in court in 1923 and established the concept of general acceptance for admission of forensic evidence.
Daubert et al., v. Merrell Dow Pharmaceuticals in 1993 set new relevancy tests and gave judges a gatekeeping role for admission of evidence. Of note is the emergence of DNA profiling, which has survived extensive court challenges and is now considered a robust, reliable, validated technology (Jeffreys, 2005, p. 1037). DNA is more reliable than either eyewitness testimony or criminal confessions (Walsh, 2005).
On a more personal note, I wonder how many I-Os nurtured an early interest in science through reading Sherlock Holmes, Nancy Drew, the Hardy Boys, and other detective stories?
The Job of Forensic Scientist
Forensic scientists manage and interpret data, reconstruct the events of crimes, and present results in court. In this technologically fluid environment, the trend is toward increased specialization; generalist training is declining, although not without criticism (see Rudin & Inman, 2001). Routine collection of evidence, such as human physiological fluids, ballistic cartridges, and latent prints, is shifting to police personnel in the field, often using mobile crime lab units. Crime scene evidence is submitted and analyzed through laboratory information management systems (LIMS) using electronic data; batch processing and robotics reduce cycle times.
CSI aside, forensic science jobs lack the glamour portrayed in the media. Chronic staff shortages and low wages are systemic. The field faces major staffing hurdles. The difficulty attracting and retaining competent forensic scientists within the constraints of the civil service system was noted a half century ago (OHara & Osterburg, 1949). Salaries are not competitive and public labs often serve as training grounds for the private sector. On-the-job apprenticeships of at least 1 year are required to develop forensic scientists. Senior scientists can experience productivity declines of up to 50% while training new employees. Surprisingly, the use of realistic job previews is limited, despite extensive preemployment testing (Becker & Dale, 2003).
Employee turnover is problematic (Hines, 2005; Perlman, 2004; Rondeaux, 2003; Rosetta, 2005). The case study of a large northeastern state crime lab is illustrative (Dale & Becker, 2004). A new staffing model created the support position of laboratory technician to perform routine duties in the lab so that data interpretation and more complex tasks could be reserved for forensic scientists. The proposal for the two-tiered structure estimated saving the organization $1 million. After 1 year, 16 of 53 newly hired employees left the organization. Costs associated with the early departure of these employees exceeded the proposed savings and the experiment was considered a failure. Exit interviews revealed that laboratory technicians had anticipated a rapid move into forensic scientist positions. However, when technicians learned that promotional opportunities were limited, many left the organization, often for private sector jobs.
Professional development opportunities are critical for retention yet the career motivations of technical workers are not well understood (Von Glinow, 1988). In crime labs, support for professional development may include tuition reimbursement, flexible work hours, support for professional meetings, seminars and conferences, and training in more than one discipline, such as a primary area like latent prints and a secondary area like footprints.
A relatively new strategy is to convene a special forensic advisory group for on-the-job professional development (Dale & Becker, in press). Forensic advisory groups consist of experienced and retired forensic professionals from various technical disciplines and the academic community; members are chosen for their ability to build trust and share knowledge with laboratory staff. Available through phone calls, e-mails, and review meetings, forensic advisory group members help to create a culture of mentoring and collaboration for staff, who may otherwise be isolated in their labs. The forensic advisory group resides in the lab for a specified period of time (for example, 1 week) providing developmental feedback to employees. Coaching is provided to testifying scientists for communicating expert opinions with integrity and confidence. The relationship between innovative management strategies, such as forensic advisory groups, and lab performance must be further explored.
Linking Management Practices to Lab Outcomes
The consequences of performance errors in this industry are severe and state lab systems have been shut down for failures in work quality (Dao, 2005; Perlman, 2004; Preston, 2005). Highly publicized incidents have involved both individual employees and entire systems. For example, the Federal Bureau of Investigation (FBI) laboratory was cited in 1997 for scientifically flawed testimony, testimony beyond the competence of examiners, improper preparation of lab reports, insufficient documentation, inadequate record management, and failure of management to resolve allegations of incompetence (Giannelli, 2003). The need for laboratory standards was noted in the first serious challenge to DNA evidence in 1987
(New York v. Castro). In the U.S., the industry regulates itself through the American Society of Crime Laboratory Directors Laboratory Accreditation Board (ASCLDLAB). As a personal aside, participating in a preaccreditation audit is a worthwhile experience for an I-O.
Much work remains to be done establishing direct links between employee behaviors and lab outcomes. Table 1 provides proposed measures of employee performance that can be used uniformly across labs. In addition, crime labs need accurate measures of the value of the services that they provide to the community (Avery, 2000). One example is determining that the market value of a DNA profile is worth $1,000 (Dale & Becker, 2004). In
addition, staffing needs can be estimated based on a ratio of one forensic scientist (defined as testifying scientist) for every 30,000 people in the community (Dale & Becker, 2003). Estimates based on geopolitical populations provide a common standard across disparate units and agencies and are useful to communicate resource needs. An alternative example is to estimate the ratio of forensic scientists to police officers that results in acceptable laboratory performance for the community (Fischer, 2003). Until standardized employee measures are implemented it will be difficult to demonstrate staffing needs to obtain needed resources.
Table 1
Examples of Performance Measures
_________________________________________________________________________________________________
1. Cases/items analyzed per scientist/per project team/per laboratory
2. Ratio of local, state, and national ballistic hits in the National Integrated Ballistics Imaging Network per firearms examiner and per capita of service region
3. Ratio of local, state, and national latent fingerprint hits in the Automated Fingerprint Identification System per fingerprint examiner and per capita of service region
4. Ratio of local, state, and national DNA hits in the Combined DNA Index System per DNA scientist and per capita of service region
5. Ratio of technical support personnel per capita of service region
6. Total cost of analyses per case and per item
7. Total cost of errors, for example, rework
8. Employee turnover
9. Quality system measures, including:
a. Number of corrective actions
b. Number of types and frequency of corrective actions per discipline over time
c. Number of errors per case, per item
d. Timeliness of analyses
e. Total backlog
____________________________________________________________________________________
(Dale & Becker, in press)
Stressful Work Environment
Crime labs are interesting organizations to study. There is a zero tolerance for mistakes, an unpredictable work flow, and constant backlogs (Sewell, 2000). Labs are hierarchical, quasi-military operations, typically housed within police departments. Police agency demands can divert attention from the needs of the lab in favor of patrol vehicles and police officers. Scientists report to sworn officers, who may not fully understand technical scientific issues. There are often no career paths provided for forensic scientists, other than traditional police ranks of lieutenant, captain, major, and so forth (Kanable, 2005).
Team structures offer advantages yet remain underutilized. As an example, DNA processing currently involves an inefficient boutique method of case work analysis: One scientist performs all the tasks needed to complete a case. Implementing high-performance team models along with recent innovations in batch processing and computer expert systems would dramatically improve productivity (Dale & Becker, in press). For example, a multidiscipline case might involve ballistic, hair, fiber, and DNA evidence analyses. Use of project teams would ensure collaboration between the technical disciplines and facilitate communication with management.
Case Backlogs and Outsourcing
Increased demand for crime lab services has resulted in a serious case backlog. In the U.S. only one-third of the cases submitted to crime laboratories are actually analyzed, due to the case backlog (Peterson & Hickman, 2005). Labs must prioritize cases as demand for services exceeds supply. Tests needed for prosecution take precedence over tests needed for investigation, so high-profile and violent crimes are processed, but crimes with no suspect are delayed. There are serious consequences and the Washington D.C. snipers in 2002 serve as an example. The two criminals could have been identified earlier in their cross-country crime spree because information from their previous crimes existed in national databases. But case backlogs delayed the processing of evidence, and the snipers remained free to commit more crimes (Halbfinger, 2002).
Because of backlogs 41% of public crime labs outsource cases to private labs (Peterson & Hickman, 2005). Government grants provide funding for outsourcing cases but not permanent hiring (Koussiafes, 2004). However labs are often reluctant to rely on outside help. Even though 79% of a national sample of U.S. labs did not have a sufficient number of scientists, the majority (71%) would not send more cases to private labs even if they had extra funding available (Becker, Dale, Lambert, & Magnus, 2005). Employees would rather work on their own to resolve case backlogs, as a matter of pride. One lab director stated that employee performance in his lab increased dramatically when the lab began outsourcing. Understanding employee pride of ownership in forensic work could be profitably explored.
Better Labs Can Mean Reduction in Crimes
Labs have difficult and diverse external customers, such as district attorneys, detectives, crime victims, and the local community. High-profile crimes demand quick processing of evidence.
Increased lab productivity would help stop criminals earlier in their criminal careers. The implicit theory is that offenders identified as a result of minor criminal activity do not advance to more serious crimes (Simon, 1997; National Institute of Justice, 2003). Ninety-four percent of convicted offenders previously committed minor crimes (Haapanen, 1998). In one study, felons whose most serious prior convictions were for forgery or passing bad checks had DNA matches in 12 rape cases, 8 homicides, 1 rape-homicide, an assault, a robbery, and a car jacking
(Specialists want to expand state DNA database, 2003). This situation presents an opportunity for better understanding of relationships between employee measures and societal outcomes. The implication for well-staffed, quality-driven crime labs includes a reduction of crime nationwide.
Implications for the Future
The 21st century is the century of DNA, promising profound change to all the sciences including psychology (Plomin & Crabbe, 2000). Technological innovations, such as accelerated testing and miniaturization of evidence samples, teleforensics, data mining, digital documentation, and expert system models are transforming the job of forensic scientist (Jeffreys, 2005; Kanable, 2005). The future will see expansion of internationally integrated databases, although not without heated discussions about the appropriate balance between privacy and public safety, and the potential for misuse of data.
In the U.S., analysis of DNA evidence post-conviction has exonerated 174 wrongly convicted individuals and is playing a significant role in restructuring the criminal justice system (see for example, FBI Combined DNA Index System; Innocence Project). In the UK, efforts are underway to overhaul forensic science into an independent scientific institute, making results of analyses available to those on both sides of a criminal case (Page, 2003).
The psychological factors are as important as technology to the future of the forensic sciences. Behavioral scientist perspectives must complement the impressive advances in crime lab technology. The future of this industry depends on overcoming case backlogs and increased demand for services, transitioning to automated systems, and making the best use of information databases and new technology. Well-educated, trained, and competent employees are critical to this vision. I-Os have much to offer for reinventing the crime lab.
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Cases Cited
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Frye v. United States (D.C. Cir. 1923) 293 F. 1013.
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