Crime, Law and Social Change

, Volume 65, Issue 1, pp 67–91

Public knowledge about white-collar crime: an exploratory study

  • Cedric Michel
  • John K. Cochran
  • Kathleen M. Heide

DOI: 10.1007/s10611-015-9598-y

Cite this article as:
Michel, C., Cochran, J.K. & Heide, K.M. Crime Law Soc Change (2016) 65: 67. doi:10.1007/s10611-015-9598-y


A growing body of research has revealed that the financial cost and physical harmfulness of white-collar crime overshadow the impact of street crime on society. To date, scholarly efforts that have investigated societal response to crimes of the powerful have limited their field of inquiry to public opinions about white-collar crime. Although these studies have provided valuable empirical evidence of a growing concern among U.S. citizens regarding the danger posed by elite offenses, their failure to include a valid measure of lay knowledge about white-collar crime significantly limits our ability to infer the extent to which the public is familiar with the scope and magnitude of this social issue. The present study seeks to address such limitations by providing the first measure of public knowledge about white-collar crime. Four hundred and eight participants completed an online questionnaire that measured their knowledge about white-collar crime. Results revealed that participants were not sufficiently informed about it and suggest the existence of popular “myths” about crimes of the powerful. These findings have important implications insofar as white-collar crime awareness programs are concerned. Hypothetically, public demand for tougher sanctions against high-status offenders could result from exposure to relevant information about white-collar crime. Nevertheless, “myth” adherence might also undermine the effect of increased awareness on prosecutorial efforts against upper-class criminality.

Research has established that the social impact of white-collar crime greatly exceeds that of street crime, both in terms of financial costs and physical harmfulness. More specifically, traditional property offenses such as burglary and theft cost the public about $18 billion each year [1]. In contrast, annual losses due to large-scale white-collar crime (including various forms of fraud and health costs caused by work-related injuries and illnesses as well as environmental pollution) are way above a trillion dollars [2, 3, 4, 5, 6, 7]. Further, compared with the 14,000 people who lose their lives to murder and nonnegligent manslaughter every year [1], an estimated 300,000 die annually as a result of work-place related accidental injuries due to the company’s negligence, illnesses caused by prolonged exposure to toxic chemicals, toxic waste dumping and deadly pollutants, faulty consumer products, nefarious and addictive substances, as well as medical malpractice [6, 7, 8, 9, 10, 11].

Despite these staggering differences, however, white-collar crime is still less prosecuted than street crime. In fact, corporate regulations are weak, the culpability of corporations harder to prove for prosecutors, and sentences for corporate offenders have up until recently typically been more lenient compared to those imposed upon street criminals [12, 13, 14, 15, 16]. Criminologists are aware of these blatant discrepancies, but the extent to which the general public is remains uncertain. Indeed, not one study has provided a direct measure of popular knowledge about white-collar crime. The purpose of the present paper is to fill this gap. But before we can provide a clear rationale for doing so, the key variable that we propose to measure must be conceptually defined. This is no easy task, however, as the very definition of white-collar crime has been the subject of much academic debate.

Conceptual ambiguity

Building upon Ross’s criminaloid concept [17], Sutherland [18] called white-collar crime “crime committed by a person of respectability and high social status in the course of his occupation”. His provocative conceptualization of criminals wearing the proverbial white collar - a symbol of professional success as opposed to working-class employees’ blue collar - was a landmark in the history of criminology. Until then, the field had maintained its focus on offenses generally associated with the lower class. By arguing that upper-world criminality was not only more deleterious to society but also less likely to be reported and punished, Sutherland provided fertile grounds for subsequent theoretical approaches.

Over time, though, considerable confusion in the literature has grown regarding the true nature and extent of white-collar crime. Tappan [19] observed that white-collar offenses were not dealt with by traditional criminal justice systems but by administrative courts. He therefore opined that referring to them as “criminal” offenses was not only technically incorrect but also driven by ideological and political motives. Further, scholars have denounced Sutherland’s original definition as “vague” [20], “inadequate” [21], and “ambiguous”, reasoning that it does not distinguish crimes committed by individuals within organizations from those actually perpetrated by corporations [22]. Other critics have pointed out that it could encompass both occupational crimes (i.e., acts committed in the course of one’s occupation for personal gain) and avocational crimes (i.e., acts that are usually unconnected with one’s profession such as income tax evasion or credit card fraud, [23]). Similarly, Edelhertz [21] lamented Sutherland’s foci on status (upper class) and location (working place), and instead suggested to concentrate on actual behaviors. This lack of conceptual clarity led the FBI to count as white-collar offenses many crimes actually committed by middle-class workers [24]. Ironically, Sutherland himself fell victim to his concept’s ambiguity when most of the data that he collected to test his theory were obtained from lower-level offenses such as workplace theft, deception by mechanics and shoe salesmen, etc. [25]. Perhaps as a result, Strader [26] has called the term “white collar” a misnomer, arguing that these crimes can be perpetrated among the working class (e.g., scams, retail crime, tax evasion, etc.) as much as within the upper class (e.g., antitrust violation). According to her, the term is a useful moniker to differentiate nonviolent crime for financial gain committed by means of deception (e.g., securities fraud) from more common (i.e., street) crime in the public mind. Similarly, Brightman [27] has argued that the white-collar crime construct should only include nonviolent acts committed for financial gain, regardless of one’s social status.

Perhaps the economic changes that took place during the twentieth century were responsible for causing scholars to misconstrue Sutherland’s message. Because the United States has shifted from an industrial to a service economy, the nature of the job market is now quite different from what it was back in the 1940s. Today a postal clerk may well don a white collar but can hardly be considered a person of “high social status”. In fact, an employee embezzling a few hundred dollars from his/her company may share more similarities with a street offender than with the powers-that-be denounced by Sutherland. If one defines power in terms of economic control (i.e., ownership of the means and modes of production) and political clout, then, respectable but relatively powerless figures (e.g., bank tellers, accountants, etc.) that would be considered white-collar offenders according to the UCR do not quite fit Sutherland’s original definition. On the other hand, offenses of greater social harm (i.e., those actually committed by persons of high social status in the course of their occupation) are virtually absent from official data collected by law enforcement agencies nationwide.

How to explain this double standard? As Becker [28] noted, “social groups create deviance by making the rules whose infraction constitutes deviance, and by applying those rules to particular people and labeling them as outsiders”. Since illegality is determined by a distinct group of officials (i.e., the legislature), the same individuals who label and prohibit street crime may be tempted to overlook upper-world offenses (e.g., war profiteering, government corruption, large-scale fraud, or toxic dumping) to protect powerful interests. Consequently, corporations can engage in unethical behaviors (i.e., intentional, reckless, and negligent) that are not legally defined as criminal (e.g., regulatory offenses) even though they may kill and injure more people every year than do street crimes - with little fear of legal consequences [6].

As previously mentioned, however, it is unclear to what extent the public is aware of upper-class criminality. The few studies (e.g., [29, 30, 31, 32, 33, 34]) that explored public awareness of crime have mostly focused on street crime and largely ignored white-collar crime. These empirical efforts have identified several “myths” such as increasing crime rates [32], violent crime rates increasing faster than property crime (Knowles [35]), overly high recidivism rates [30], and the deterrent effect of the death penalty [29,36]. While these “myths” have been debunked by existing research, they remain solidly anchored in the public psyche and belie a distorted view of the reality of crime marked by an overestimated perceived risk of victimization [33,37].

Because the majority of public knowledge about crime and justice is derived from the media [38, 39, 40], it could be that news outlets do not perform their duty of disseminating scientific knowledge to the public. Moreover, street crime is given disproportionate coverage, both in newspaper headlines and in local television news, compared with white-collar crime [6,41, 42, 43, 44, 45]. Political and corporate elites - who greatly influence the editorial content of mainstream media - can easily exploit such mechanisms to exaggerate the “conventional” crime problem while downplaying the harm they personally cause. Consequently, given the public’s limited exposure to accurate information about white-collar crime in the media, people might indeed harbor “myths” about crimes of the powerful as they do regarding street crime. Nevertheless, this hypothesis has never been directly tested because most white-collar crime and public perceptions research has focused on public opinion rather than public knowledge. This limitation does not allow us to estimate the effect of awareness (or lack thereof) on perceived seriousness of white-collar crime and punitiveness toward its perpetrators.

Public opinion about white-collar crime

The evolution of public opinion about white-collar crime can be divided into three distinct periods [46]. Each of these three waves reflects gradual changes in attitudes, from widespread ambivalence to increased intolerance, which were captured by empirical research. The first wave spanned the major part of the twentieth century and was characterized by relative inattention to the problem. As early as 1907, Ross had taken issue with the public’s apparent ignorance or (worse yet) indifference about business crime. Similarly, Sutherland [18] lamented the people’ s lack of objective information and refusal to consider white-collar offenses as equivalent to traditional street crime.

Nevertheless, subsequent research (e.g., [47, 48, 49]) attempted to debunk the notion of public apathy about white-collar crime. For example, Conklin [47] argued that there existed a greater degree of public condemnation of business crime than was previously assumed. He also conceded, however, that the public seemed more concerned and punitive when prompted with a survey describing specific white-collar crime scenarios, which cast doubt regarding respondents’ prior knowledge about the issue. Further, he concluded that while morally obligated to condemn the instances of business crime presented to them, participants did not seem to relate to upper-world criminality. Such underestimation of the risks posed by crimes of the powerful suggested a significant lack of public knowledge, a hypothesis seemingly supported by Reed and Reed’s survey of college students [50] in which subjects were either ignorant of the existence of white-collar crime or incapable of defining it.

On the other hand, the second wave of research on public opinion about white-collar crime (from the late 1970s to the early 2000s) highlighted rising attention to upper class offenses. These studies (e.g., [51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62]) concluded that (1) the public had become more aware of white-collar crime, (2) its perceived seriousness of upper-world criminality had greatly increased (especially in regard to high financial and physical harm), and (3) it was no longer opposed to bringing white-collar offenders to justice. Several factors can explain this hardening of attitudes, including a loss of trust in political and corporate institutions after such events as the Watergate scandal, the Ford Pinto case, or the Bhopal disaster, which had been reported by investigative journalists, thus making white-collar crime a household name.

A similar trend has continued to emerge during the third and final phase (i.e., the last fifteen years), a period characterized by what Cullen and colleagues [46] called transformed attention. The immediacy of information, made possible by technological progress in telecommunication, allowed for a more direct and intense coverage of large-scale corporate, financial and environmental scandals like the Enron and WorldCom debacles, Bernie Madoff’s Ponzi scheme, and the BP oil spill. Perhaps unsurprisingly, studies on public attitudes about white-collar crime revealed perceived seriousness of these offenses and punitiveness toward their perpetrators to have reached new heights (e.g., [63, 64, 65, 66, 67, 68, 69, 70, 71, 72], etc.). In a recent study, Internet users were found to be more likely to be knowledgeable about white-collar crime, which is not a common topic of interest in the corporate-owned media. As an independent and alternative news source, the web may therefore represent a formidable educational platform as far as white-collar crime is concerned [73].

A significant part of this more recent body of research was initiated by the National White-Collar Crime Center. Every five years since 1999, this congressionally funded non-profit corporation has been surveying public attitudes about the seriousness and impact of white-collar crime. All three iterations [64,65,69] presented respondents with scenarios that described various forms of white-collar and street crime. Participants’ perceived seriousness of these offenses and punitiveness toward their perpetrators were then measured. Overall, the results suggest that the public actually considers white-collar crime to be a more serious social issue than was previously hypothesized. Importantly, subjects rated several examples of white-collar crime as more serious than a traditional street crime like motor vehicle theft, and deserving of stiffer punishment. Perhaps, then, punitiveness is a function of knowledge. However, this suggestion is mere conjecture since no study, to date, has provided a measure of what people really know about white-collar crime.

The present study

The National White-Collar Crime Center survey was limited by its failure to control for its participants’ knowledge. While respondents’ negative attitudes toward the scenarios submitted to them suggest a reasonable amount of education, the true extent of information among the public, particularly in regard to the physical harm of white-collar crime, remains uncertain. Public awareness in these studies was only inferred, and it is unclear whether punitive sentiments observed in the various iterations of the survey were due to years of exposure to sensitive information on the subject or simply to vignettes that described harmful activities previously unknown to the participants.

Further, the surveys developed by the National White-Collar Crime Center, which was funded by Congress - one of the power elite groups identified by C. Wright Mills [74] - included many low-level offenses (e.g., counterfeit sales, insurance overcharge, identity theft, etc.). Accordingly, the questions explicitly followed offense-based rather than offender-based definitions of white-collar crime. As such, the instruments were not faithful to Sutherland’ s definition.

For all these reasons, measuring public knowledge about white-collar crime would make a significant contribution to the field. The present study therefore expands research on public response to white-collar crime by providing a much-needed measure of popular knowledge about upperworld criminality. The following research questions will be addressed:
  1. 1)

    Is there a gap between the public’s subjective and objective knowledge about white-collar crime?

    By “subjective” knowledge, one must understand what people think they know about white-collar crime. Conversely, “objective” knowledge refers to how informed they truly are. Several studies have identified a gap between the public’s subjective and objective knowledge about risks of victimization (e.g., [30, 31, 32, 33, 34]). Such discrepancy was also observed with measures of public information about capital punishment [29,36,75]. More specifically, those studies revealed that the public was not as informed about issues related to the death penalty as they thought they were. Therefore, there might be a similar gap between what individuals think they know about white-collar crime and their actual level of information regarding white-collar crime.

  2. 2)

    To which extent is the public informed about white-collar crime?

    The field of epistemology (i.e., the branch of philosophy concerned with the study of knowledge) differentiates truth (evidence-based information) from belief (non-evidence-based opinion). One proposition is that knowledge may be better understood as justified true belief [76]. That is, a belief becomes knowledge if it is both believed to be true and currently supported by extant research. Knowledge about white-collar crime will therefore be conceptualized and operationalized as statements that according to extant research are commonly regarded as valid (e.g., superior harmful costs to society compared with street crime). As previously mentioned, since most U.S. citizens derive their information from the news media, and because the news media do not report on cases of white-collar crime as vigorously as they do on street crime, it is plausible to expect that the public is not well educated about the various dimensions of such a multifaceted construct (e.g., types of harm, of offense, of offender, etc.).

  3. 3)

    Does the public hold common “myths” about white-collar crime like they do regarding street crime?

    We propose to conceptualize and operationalize knowledge about white-collar crime as statements that according to extant research are commonly regarded as valid. Conversely, unsubstantiated beliefs and arguments that have been debunked by science (but which the public might still commonly believe) constitute white-collar crime “myths”. As previously mentioned, research has identified public “myths” about street crime and the criminal justice system (e.g., [29, 30, 31, 32, 33, 34, 35, 36,75]). While it is true that white-collar crime is occasionally given front-page coverage (e.g., the Enron debacle, Martha Stewart’s insider trading, Bernard Madoff’s Ponzi scheme, etc.), its presentation in the media is still limited compared with that of street crime. Further, more emphasis is placed on nonviolent cases, which may mislead the public into thinking that upper-world offenses represent more of a financial threat than a physical one [42]. Consequently, it is very likely that the public harbors specific “myths” regarding white-collar crime, and the physical harmlessness of white-collar crime compared to street crime could be one of them. This study will therefore attempt to identify other such “myths”.



Sample selection

The subjects in this study were recruited on Amazon’s Mechanical Turk, a web service that coordinates the supply and demand of human intelligence tasks (HIT). More precisely, requesters post HITs that can be completed on a computer (e.g., a social science survey), and participants (known as “Turkers”) volunteer to complete them based on the size of the reward (i.e., a small payment) and maximum time allotted for the completion. Mechanical Turk has recently become popular in criminology (see, e.g., [77, 78, 79, 80]) as a source of data collection due to its convenient recruitment and low cost.

Mechanical Turk presents several advantages compared with other data collection methods. Since there are no travel costs, and because “Turkers” choose when they want to complete tasks, the effort that must be expended to participate is much lower than in lab-based experiments. Further, research suggests that data collected on Mechanical Turk are as reliable as those obtained via traditional methods. More specifically, Paolacci and colleagues [81] replicated standard judgment and decision-making experiments among subjects recruited on Mechanical Turk, online discussion boards, and at a large university and found the results to be qualitatively identical. In addition, “Turkers” are at least as representative of the U.S. population as traditional subject pools, with gender, race, and age all matching the population more closely than college undergraduate samples and Internet samples in general [81,82].

Data collection procedure

Data collection took place on April 1st, 2013. Prior research suggests that recruiting 500 subjects on Mechanical Turk for a social science experiment is a realistic goal (see, e.g., [82]). Paolacci and colleagues [81] posted a task that required workers to answer a 5-minute survey for $0.10 and were still able to attract 131 workers. Because the instrument to be used in the present study was twice as long and admittedly more complex, a monetary incentive of $2.00 per respondent was proposed to maximize completion rate. The sample size goal of 500 adult American participants was reached within only three hours.

Participants were asked to complete an online questionnaire approved by the Human Subjects’ Review Board at the lead author’s former university. This questionnaire measured respondents’ level of knowledge about white-collar crime. Potential participants were informed that their answers would remain confidential. Overall, they rated the experience favorably. More specifically, several subjects took the time to email the author to comment on the interest they took in the survey’s topic and expressed their desire to seek out further information about white-collar crime. While the system ensured that respondents would not be able to complete more than one survey, they were compensated even for partial completion. Eliminating incomplete and/or dubious surveys as well as those completed too quickly (pilot testing showed that completion time was about 10 minutes) yielded a final sample of 408 participants.

The demographic characteristics of the sample were somewhat representative of the overall United States population. The 2010 United States Census indicates that the national median age is 36.8, that 50.8 % of U.S. citizens are females, that 78 % identify as Whites, 13.1 % as Blacks, 1.1 % as Middle Eastern, 1.2 % as American Indians or Alaskan Natives, 5 % as Asians, 0.2 % as Native Hawaiians or Pacific Islanders, and 16.7 % as Hispanics. Comparatively, the median age in this study was 31, 49.8 % of the respondents were female, 83.6 % of them identified as Whites, 8.8 % as Blacks, 0.5 % as Middle Eastern, 0.5 % as American Indians or Alaskan Natives, 5 % as Asians, 0.2 % as Native Hawaiians or Pacific Islanders, and 6.9 % as Hispanics. Further, the median annual household income was between $40,000 and $49,000 (i.e., slightly lower than the national estimate of $52,762). College graduates (Bachelor’s degree or higher) accounted for 49.5 % of the total sample (against only 28.2 % at the national level), and 41.7 % of the respondents were employed full-time (against 44.1 % of the overall population). Despite discrepancies regarding age, race/ethnicity, and education, it therefore appears that the sample in this study still followed national trends closely in terms of gender, household income and employment status distribution.


Knowledge about white-collar crime was measured via a two-pronged approach. More specifically, the instrument included measures of both subjective and objective knowledge. Table 1 presents descriptive statistics for the following variables.
Table 1

Descriptive Statistics (n = 408)






Subjective Knowledge

4-point ordinal scale




(1 = Not informed;

4 = Very informed)

Source of Information

Dummy variable


- 0 = Traditional media


- 1 = Internet




Previous Exposure to Information about

0 = Never been exposed




White-Collar Crime

1 = College course



2 = Movie/TV series



3 = Documentary



4 = Television news report



5 = Newspaper article



6 = Book



7 = Internet



8 = Other



Objective Knowledge

10-item multiple-choice and true or false questionnaire


- Meaning of the term


- Financial cost




- Harmfulness




- Legal immunity




- Reckless disregard




- Medical crime




- Human trafficking




- State-corporate crime




- Toxic dumping




- Toxic emissions




Answer Confidence

4-point Likert-type confidence scale (1 = Not at all confident; 4 = Very confident)


- Meaning of the term




- Financial cost




- Harmfulness




- Legal immunity




- Reckless disregard




- Medical crime




- Human trafficking




- State-corporate crime




- Toxic dumping




- Toxic emissions





Correct answer + confident or very confident


- Meaning of the term




- Financial cost




- Harmfulness




- Legal immunity




- Reckless disregard




- Medical crime




- Human trafficking




- State-corporate crime




- Toxic dumping




- Toxic emissions





Incorrect answer + confident or very confident


- Meaning of the term




- Financial cost




- Harmfulness




- Legal immunity




- Reckless disregard




- Medical crime




- Human trafficking




- State-corporate crime




- Toxic dumping




- Toxic emissions




Subjective knowledge

Subjective knowledge was measured several ways. First, respondents were asked to self-assess the degree to which they felt they were informed about white-collar crime (1 = Not informed, 2 = Somewhat informed, 3 = Informed, 4 = Very informed). Importantly, the participants were also asked about their primary sources of information (1 = Television news stations, 2 = Radio news stations 3 = Newspapers, 4 = Magazines, 5 = Books, 6 = Internet, and 7 = Other). Based on the subjects’ answers, the following dummy variable was then created (0 = traditional media, 1 = Internet). Second, subjects were asked whether they previously had been exposed to relevant information about white-collar crime, and if so what medium they used to educate themselves (1 = College course, 2 = Movie/TV series, 3 = Documentary, 4 = Television news report, 5 = Newspaper article, 6 = Book, 7 = Other, and 8 = I have not been exposed to such information). Lastly, participants were asked how confident they felt about their answers to an objective knowledge questionnaire (1 = Not at all confident, 2 = Somewhat confident, 3 = Confident, and 4 = Very confident). This questionnaire is described in greater detail in the following section.

Objective knowledge

Objective knowledge was measured via a 10-item questionnaire that included multiple-choice and true or false questions largely derived from the bank of test items developed for Rosoff, Pontell and Tillman’s text Profit Without Honor: White-Collar Crime and the Looting of America [83]. One caveat when developing valid and reliable measures of public knowledge is to craft questions that are reasonably understandable to a large number of people with response options that are not too specific. Rosoff and colleagues’ test bank was originally supposed to be administered to students enrolled in a college course on white-collar crime. As such, it may not work well with a more heterogeneous population with probably little previous exposure to relevant information about white-collar crime. To address this problem, only those items that tapped broad dimensions were selected while those that focused on specific examples and used precise figures in their response options were deliberately excluded. Moreover, several questions and answer options had to be rephrased to make them more accessible to a non-educated audience. The questionnaire tapped the following dimensions of white-collar crime:

Meaning of the term “white-collar” crime

The first dimension is the meaning of white-collar crime. In order to determine whether the public understands Sutherland’s reference to the metonymic white collar to describe high social status offenders, respondents were asked what the term “white-collar crime” was based on. Response options included: “The types of victims”, “The occupations of the perpetrators”, and “The offenders’ association with religion”.1

Financial cost

The second dimension is the financial cost of white-collar crime, which was measured by asking respondents how much street crime cost the public compared to white-collar crime. Response options included “Significantly less”, “Somewhat less”, “The costs are about the same”, “Somewhat more”, and “Significantly more”. As previously mentioned, conservative estimates place the financial impact of white-collar crime about 50 times above that of traditional crime [2, 3, 4, 5, 6, 7].


The third dimension is the physical harmfulness of white-collar crime and was measured by asking subjects how likely street crimes like assaults, murders, and muggings were to injure or kill people compared with white-collar crime. Response options were: “Significantly less likely”, “Somewhat less likely”, “As likely”, “Somewhat more likely”, and “Significantly more likely”. Again, research indicates that the physical danger posed by white-collar crime leads to the untimely death of 20 times more people compared with criminal homicide [6, 7, 8, 9, 10, 11].

Legal Immunity

The fourth dimension is the relative legal immunity enjoyed by white-collar offenders compared with street criminals [13,15,84], and was measured by asking subjects how likely someone who committed a street crime like burglary and stole $1000 was to be convicted and to receive a similar sentence as someone who committed a white-collar crime like fraud and stole $1000.2 Response options were: “Significantly less likely”, “Somewhat less likely”, “As likely”, “Somewhat more likely”, and “Significantly more likely”. Although recent research suggests a toughening of white-collar crime prosecution [16], individual offenders are still easier targets than are business organizations, possibly because establishing criminal intent for a corporation is a difficult task [12,14].

Reckless disregard

The fifth dimension is reckless disregard for human life. While corporations typically escape convictions of purposeful intent to cause harm, they can be found guilty of engaging in acts they know to be dangerous while ignoring potential harmful consequences [85]. Reckless disregard was measured by asking respondents whether the following narrative was true or false: “Although Ford knew their Pinto model’s gas tank represented a safety defect, they chose not to invest in an inexpensive and safer design, reasoning that it would be cheaper to pay out expected wrongful death lawsuits. As a result, several people died in fiery crashes.” The answer is “true” [86].

Medical crime3

The sixth dimension is medical crime and was measured by asking participants how many people in the U.S. died from medical malpractice each year compared with criminal homicides. Response options included the following: “More”, “An equal number”, and “Fewer”. Research suggests that U.S. citizens are about 15 times more likely to die as a result of medical malpractice - which can and has led to criminal charges against the medical practitioners involved [87] - than they are from criminal homicide [11].

Human trafficking

The seventh dimension is human trafficking in the United States. Subjects were asked whether the statement “Human trafficking is more common in underdeveloped countries than in developed nations” was true or false. While the public may associate human trafficking with squalid living and working conditions in U.S. company-owned Southeast Asian sweatshops, the existence of domestic slavery among foreign workers on American soil has been documented [88, 89, 90].4

State-corporate crime

The eighth dimension is state-corporate crime and was measured by presenting subjects with the following statement and asking them whether it was true: “Private American military companies have been accused of engaging in a number of human rights violations including the abuse and torture of detainees, shootings and killings of innocent civilians, destruction of property, and sexual harassment and rape”. The same statement can be found on the Amnesty International website in reference to allegations of human rights violations at the American prison camp of Abu Ghraib, Iraq and the 2007 shootings of Iraqi civilians by private U.S. security contractor Blackwater, which resulted in 17 deaths and 24 people injured.

Toxic dumping

The ninth item taps the environmental crime dimension and asked participants to determine whether landfills and toxic waste disposal sites were most likely to be located near African American communities (response options included “true” and “false”). Extant research suggests that this statement is true [91, 92, 93].

Toxic emissions

The tenth and final item also taps environmental crime and was measured by asking respondents whether toxic emissions could be reduced much more if industries agreed to employ appropriate technologies5 (response options include “true” and “false”). A relatively new paradigm concerned with the impact of environmental crime, green criminology [95, 96, 97, 98, 99, 100, 101] interprets America’s refusal to sign the Kyoto Protocol (an international treaty pledging to reduce greenhouse gas emissions), or to invest in modern, sustainable forms of energy (e.g., solar roofing in Florida) as being driven by corporate interests, simply because these progressive ventures are deemed financially detrimental to American corporations.

Each correct answer to those ten items was entered into an overall knowledge scale and a percentage of correct answers was calculated. The intent was to attribute a percent score to subjects, as would be the case if they had taken a test based on a 100-point grading scale. As with subjective knowledge, the following grading policy was used: 90–100 (10 or 9 correct answers) = “Very informed”, 80–89 (8 correct answers) = “Informed”, 70–79 (7 correct answers) = “Somewhat informed”, and below 70 (less than 7 correct answers) = “Not informed”.

“Truth” acceptance vs. “myth” adherence

Further, a measure of “truth” acceptance and “myth” adherence was provided. White-collar “myth” variables were created whenever subjects felt either “confident” or “very confident” about their answer to a knowledge item even though they chose the wrong response option. Similarly, white-collar “truth” variables were created each time participants picked the correct answer to a knowledge item while feeling “confident” or “very confident” about it. Subjects who felt “confident” or “very confident” and answered correctly are hereafter referred to as “’truth’ accepters”. In contrast, those who felt “confident” or “very confident” and answered incorrectly are referred to as “’myth’ adherers.” Subjects who felt “not confident” or only “somewhat confident” about their response yet answered correctly are classified hereupon as “lucky guessers”. Conversely, those who answered incorrectly while feeling either “not confident” or “somewhat confident” are arbitrarily referred to as “honestly uninformed”. Descriptive statistics for these three scales are also included in Table 1. Table 2 presents the classification of subjects based on the 2X2 cross-tabulation of answer correctness and confidence.6
Table 2

Classification of subjects based on the 2 × 2 cross-tabulation of answer correctness and confidence (n = 408)

Answer confidence

Answer correctness




“Truth” Accepters

“Myth” Adherers


Lucky Guessers

Honestly Uninformed


Subjective vs. Objective knowledge

As is evident in Table 3 (which compares percent subjective and objective knowledge about white-collar crime), respondents tended to overestimate their actual level of information about upper-class criminality. More specifically, while 75.5 % can be considered “not very informed” about white-collar crime, only 12.5 % clearly mentioned lacking knowledge in this area. Further, whereas 73.5 % estimated being “somewhat informed”, a mere 14.7 % objectively deserves to be referred to as such.
Table 3

Percent Subjective and Objective Knowledge about White-Collar Crime (n = 408)


Percent subjective

Percent objective


Not very informed




Somewhat informed








Very informed




Nevertheless, only 14 % estimated being either “informed” or “very informed” when in fact less than 10 % (9.8) of the sample was found to be. These findings suggest that although participants overestimated their true level of knowledge about white-collar crime, they did not feel confident enough to rate it highly.

Extent of knowledge

Table 4 provides a more in-depth report of participants’ objective knowledge about white-collar crime by presenting the percentage of subjects with scores on the overall knowledge scale. Recall that based on the classification that was adopted in this study, a score of at least 70 % (i.e., 7 correct answers) was necessary to be deemed “somewhat informed”. Only about one fourth of the sample scored above that cut-off point. Further, less than 10 % answered enough questions correctly to be considered “informed” (7.4 % answered 8 questions correctly) or “very informed” (2.4 % answered 9 or 10 questions correctly).
Table 4

Percentage of subjects with scores on the overall knowledge scale (n = 408)

Overall knowledge score

Percentage of subjects

Cumulative percent


































Since respondents were found to be, at best, superficially informed about white-collar crime, understanding their primary source of information seemed warranted. Eighty-one point one percent cited the Internet as their medium of choice for keeping informed of important issues, far above television news stations (15 %) and other traditional forms of media. However, when asked whether they had been previously exposed to relevant information about white-collar crime, only 3.2 % mentioned the Web as their prior source of knowledge. Instead, 38.5 % reported having received some form of information about the subject by watching television news reports, 12 % by reading newspaper articles, 10.3 % by watching documentaries, 9.3 % by watching movie/TV series, and only 6.6 % by taking a college course. Further, 18.1 % mentioned having never received any form of information about white-collar crime.

As previously mentioned, white-collar crime is generally underreported by the news media compared with street crime. Admittedly, so little time allotted to the coverage of white-collar crime may not suffice to thoroughly educate television audiences about this multi-faceted social issue. Since a majority of participants rely on TV news reports as their main source of information about white-collar crime, their apparent lack of knowledge about the topic is therefore not at all surprising. What remains to be seen is whether subjects were more informed about certain aspects of white-collar crime than others, and whether their level of confidence in their answers to questions tapping those specific dimensions matched their degree of knowledge.

Recall that this study’s conceptualization of knowledge relies on a fourfold classification based on the intersections of answer correctness and confidence: (1) “’truth’ accepters” (i.e., answered questions both correctly and confidently), (2) “lucky guessers” (i.e., answered questions correctly but not confidently), (3) “’myth’ adherers” (i.e., answered questions incorrectly but confidently), and (4) “honestly uninformed” (i.e., answered questions incorrectly and without confidence). Table 5 presents the percentage of subjects falling in each of these four categories along with the mean score on the overall knowledge scale, and percent correct, percent incorrect and percent confident on the ten items that comprise it. The following is a description of these data.
Table 5

Percent correct, percent incorrect, and percent confident on the overall knowledge scale and the ten items that comprise it, and “Truth” accepters (n = 134), lucky guessers (n = 90), “Myth” adherers (n = 67), and honestly uninformed subjects (n = 117)


Percent correct

Percent incorrect

Percent confident

“Truth” accepters

Lucky guessers

“Myth” adherers

Honestly uninformed









Meaning of the Term “White-Collar Crime”








Financial Cost of White-Collar Crime








Physical Harmfulness of White-Collar Crime








Legal Immunity (relative to street crime)








Reckless Disregard (Ford Pinto case)








Medical Crime (vs. homicides)








Human Trafficking (in the U.S. vs. abroad)








State-Corporate Crime (private military firms)








Toxic Dumping (African American communities)








Toxic Emissions (Reluctance to invest in clean technologies)








Percent correct

The second column in Table 5 presents the mean score on the overall knowledge scale and the percent correct on the ten items that comprise it. With an average overall score of 54.9 out of 100, the sample in this study was far from reaching the cut-off point of 70 meant to represent “somewhat informed” subjects. Nevertheless, it appears that participants’ level of knowledge varied greatly depending on which aspects of the topic they were addressing. For example, a large proportion (89.2 %) of respondents correctly indicated that the term “white-collar crime” is based on the occupation of the perpetrators. However, only 23.8 % answered that street crime costs significantly less to the public than does white-collar crime. Interestingly, very few (3.2 %) estimated that statistically, street crimes like assaults, murders, and muggings are significantly less likely to injure or kill people than are white-collar crimes. Further, only a third (32.8 %) indicated that someone who commits a street crime like burglary and steals $1,000 is significantly more likely to be convicted than someone who commits a white-collar crime like fraud and steals the exact same amount of money.

Moreover, while a large percentage (75.5 %) deemed the description of the Ford Pinto case accurate, only 38.2 % seemed to agree that more people in the U.S. die each year from medical malpractice than from criminal homicide. In addition, although less than a third (30.9 %) correctly indicated that the statement pertaining to human trafficking was false, 66.7 % got the toxic dumping question right. Lastly, an overwhelming majority of respondents correctly answered those questions that tapped the dimensions of state-corporate crime (91.2 %) and toxic emissions (97.1 %). Though necessary, participants’ correct responses are nonetheless not sufficient to provide evidence of knowledge about white-collar crime. Only by comparing subjects’ answers to how confident they felt about them can we (1) provide a valid indicator of knowledge [102] and (2) determine which of the four abovementioned categories to which subjects belong (i.e., “’truth’ accepters’, “lucky guessers”, “’myth’ adherers”, and “honestly uninformed”).

Percent confident

The fourth column in Table 5 presents participants’ percent confident in their answers to the knowledge scale. Interestingly, subjects were not very confident about their choices, even when they did respond correctly. Recall that the average overall score on the knowledge scale was 54.9. Comparatively, the average overall level of confidence was only 49.9. A closer look at each individual item reveals further gaps. While 89.2 % of the sample correctly answered the question pertaining to the meaning of the term “white-collar crime”, fewer subjects (71.8 %) felt confident about their choice. Similarly, subjects evinced little confidence in their answer to the item that tapped reckless disregard (30.1 %) compared to the 75.5 % who chose the right answer. A similar finding is echoed in the question about medical crime. More specifically, while 38.2 % picked the correct answer, only 25.7 % felt confident about their choice.

Moreover, compared to the 91.2 % who correctly indicated as true the statement that private American military companies have been accused of engaging in a number of human rights violations, only 61.2 % were confident in their answer. Likewise, while 66.7 % correctly answered the question that asked whether landfills and toxic waste disposal sites are more likely to be located near African American communities, only 39.2 % were confident about their choice. Further, while almost three fourth of the sample (74.8 %) were confident in their answer to the question that asked whether toxic emissions could be reduced much more if industries agreed to employ appropriate technologies, a much larger percentage (97.1 %) answered that question correctly.

Nevertheless, a reverse gap between answer correctness and confidence could be observed in regard to four items. More precisely, whereas only 23.8 % seemed to agree that white-collar crime is significantly more financially costly to society than is street crime, a somewhat larger percentage (27.7 %) felt confident in their answer. A similar gap emerged with the item that tapped the legal immunity of white-collar offenders compared to street criminals. More precisely, while 32.8 % found the right answer, 58.5 % were positive about their choice. Likewise, while 43.4 % were certain that they answered the item that tapped human trafficking correctly, only 30.9 % actually did.

The greatest gap that could be observed had to do with the item tapping the harmfulness of white-collar crime. Whereas very few (3.2 %) subjects correctly indicated that white-collar crime claims more lives annually than does street crime, 66.2 % of the sample were certain that they chose the correct answer. This outstanding discrepancy suggests that participants in this study had difficulty ascribing the concept of physical harm to crimes of the powerful.

Two important findings emerge from this analysis. First, as far as knowledge is concerned, participants seemed more informed about certain dimensions of white-collar crime than they were about others. More specifically, a majority of respondents were familiar with the term “white-collar crime” and its actual meaning. Further, subjects were found to be quite knowledgeable about some of the harmful activities that some corporations undertake (e.g., reckless disregard for customers’ safety, human rights violations in occupied countries, and reluctance to implement pollution-reducing policies). Nevertheless, respondents underestimated the overwhelming physical harmfulness of white-collar crime compared to street crime, and tended - albeit to a lesser degree - to downplay the former’s considerable financial burden on society. Similarly, respondents did not know (or accept) the fact that medical crime claims more lives every year than do criminal homicides, or to realize that white-collar offenders are statistically more likely than street criminals to avoid criminal prosecutions.

Second, except for a few items (tapping the harmfulness of white-collar crime, the relative legal immunity of white-collar offenders, human trafficking in developed nations and - to a lesser degree - the financial cost of white-collar crime), the percentage of questions answered confidently was systematically lower than that of correct answers. This finding suggests that respondents may not be familiar enough with the subject and might have chosen the right answers by chance alone. The next step is thus to determine the percentage of participants who qualify as “’truth’ accepters” rather than “lucky guessers”.

“Truth” accepters vs. Lucky guessers

Columns 5 and 6 in Table 5 present the percentage of “’truth’ accepters” and “lucky guessers”, respectively. Once again, while this classification refers to subjects who answered correctly, the main difference between these two categories lies in how confident participants felt about their answers. Phrased differently, whereas “’truth’ accepters” responded both correctly and confidently, “lucky guessers” did not evince such confidence and may have picked the right answers by chance alone. First of all, the overall percentage of “’truth’ accepters” (32.8 %) is larger than that of “lucky guessers” (22.1 %). That is, the proportion of subjects who answered correctly while feeling confident about their choice was generally greater than that of participants who chose the right answers as a result of a guess. Such gap is particularly noticeable in regard to the items tapping the meaning of the term “white-collar crime” (66.9 % of “”truth’ accepters” vs. 22.3 % of “lucky guessers”), legal immunity (27.2 % vs. 5.6 %, respectively), state-corporate crime (60.3 % vs. 30.9 %), and toxic emissions (73.8 % vs. 23.3 %).

However, the gap is reversed with the items tapping reckless disregard (27.5 % of “’truth’ accepters” vs. 48 % of “lucky guessers”), medical crime (13.2 % vs. 25 %), human trafficking (11 % vs. 19.9 %), and toxic dumping (31.4 % vs. 35.3 %). That is, for these items, it appears that luck more than actual knowledge can explain correct answers. Discrepancies are nevertheless far less visible with the items that tapped the financial cost (13.7 % vs. 10.1 %) and harmfulness (2.7 % vs. 0.5 %) of white-collar crime. Recall that participants scored particularly poorly on the question pertaining to the greater physical harmfulness of white-collar crime compared to street crime (only 3.2 % answered it correctly). However, 66.2 % were confident about their answer, a finding consistent with the “myth” adherence taxon used in this study. The next step is therefore to distinguish “’myth’ adherers” from those subjects who were “honestly uninformed”.

“Myth” adherers vs. Honestly uninformed subjects

The third research question asks whether the public adheres to “myths” about white-collar crime as it does with street crime. Again, “myth” adherence in this study is operationalized as an incorrect answer held with confidence. Columns 7 and 8 of Table 5 present the percentage of “’myth’ adherers” and “honestly uninformed” subjects, respectively. The overall proportion of respondents who gave incorrect answers without feeling confident about their choice (28.6 %) was greater than that of respondents who adhered to “myths” (16.5 %). Such gap was larger for those items that tapped the financial cost of white-collar crime (62.2 % vs. 14 %), legal immunity (42 % vs. 25.2 %), reckless disregard (21.8 % vs. 2.7 %), medical crime (49.3 % vs. 12.5 %), and toxic dumping (25.5 % vs. 7.8 %), and smaller in regard to state-corporate crime (7.8 % vs. 1 %), the meaning of the term “white-collar crime” (5.9 % vs. 4.9 %), human trafficking (36.7 % vs. 32.4 %), and toxic emissions (1.9 % vs. 1 %). However, the gap was reversed with the item that tapped the harmfulness of white-collar crime; more specifically, the percentage of subjects who gave a wrong answer while stubbornly sticking to their positions was almost double that of participants who answered incorrectly yet with no confidence (63.5 % vs. 33.3 %, respectively).

It therefore appears that the crux of the concept of “myths” about white-collar crime lies within the dimensions of physical harmfulness, human trafficking, and legal immunity. One may discern two interesting patterns from these findings. First, an important number of subjects seem to share a deeply rooted notion that white-collar crime represents more of a financial threat to society than a physical one. Second, some answers suggest trust in the institutions of the American criminal justice system belied by subjects’ apparent reluctance to admit that U.S. corporations, though believed to engage in unethical acts abroad, can do the same in the United States with relative impunity.


The present study sought to fill a gap in the literature on public response to white-collar crime by providing the first measure of public knowledge about white-collar crime. More specifically, this project proposed to (1) determine whether a gap exists between subjective (perceived) and objective (actual) knowledge about white-collar crime, (2) measure the extent of public information about white-collar crime, and (3) investigate the possible existence of popular “myths” about white-collar crime akin to public misconceptions regarding street crime (e.g., crime being rampant, overly violent, etc.). Results of statistical analyses provided the following answers to these three research questions:
  • Question 1: Subjects tended to overestimate their knowledge about white-collar crime. A comparison of answer correctness and confidence, however, revealed a relative lack of certitude among participants regarding their awareness of the problem, suggesting that the concept of white-collar crime and its various dimensions may still be arcane to many people. In fact, about 20 % of the sample admitted having never received any kind of information about it.

  • Question 2: Overall, participants’ level of information about white-collar crime was low and erratic. They seemed knowledgeable about the meaning of the term “white-collar crime”, the reluctance of some companies to invest in cleaner forms of energy, the calculated endangerment of consumers for profit, and about corporate human rights violations abroad. Conversely, they were found to be rather uninformed about medical crime and the relative legal immunity enjoyed by white-collar offenders compared with street criminals. Further, though prone to recognize the greater financial cost of white-collar crime compared with traditional crime, they had difficulty estimating the true extent of such disparity.

  • Question 3: Despite their self-doubts regarding their acquaintance with the topic of white-collar crime, respondents were not inclined to acknowledge hard-earned empirical evidence such as the greater physical harmfulness of white-collar crime over street crime, and to recognize that some upper-class offenses, which they admit are common in underdeveloped nations (e.g., human trafficking), can be committed in the United States with little to no legal repercussion for the perpetrators. Although they did not directly measure their respondents’ knowledge about white-collar crime, Holtfreter and colleagues [63] nonetheless identified similar misconceptions about the relative legal immunity enjoyed by white-collar offenders. In their study, participants who felt unsafe from being victimized by a violent crime like robbery were more likely to perceive white-collar criminals as having an equal or greater chance of being caught and more harshly punished than street offenders. Such misguided opinion provides support for the hypothesis that the public may harbor “myths” about white-collar crime as they do regarding street crime.


This study has several limitations. One of them is the arbitrary taxonomy used to categorize subjects in regard to their level of knowledge about white-collar crime (i.e., “’truth’ accepters”, “lucky guessers”, “’myth’ adherers”, and “honestly uninformed”). Such typology does not capture the role unconscious knowledge may have played among subjects who seemingly guessed correctly on the knowledge questionnaire. In the field of cognitive psychology, unconscious knowledge is defined as knowledge individuals have, and could very well be using, but of which they are not aware (e.g., [103,104]). While this hypothesis is beyond the scope of the present study, future research may want to refine the classification system used here by including measures of metaknowledge (i.e., knowledge about knowledge, [105]) about white-collar crime to determine whether “lucky guessers” might actually be already informed about upper-class criminality while being unable to specify how they acquired such information.7

Another source of concern it the potential threat to construct validity. Instead of measuring knowledge, questions that forced subjects to choose between only two response options (e.g., true or false) might have inadvertently led them to guess correct answers. In addition, the use of subjective response options such as “somewhat more/less” and “significantly more/ less” is problematic when assessing objective knowledge might vary by individuals. Future replications of this study should include a range of figures for respondents to select.

Nevertheless, even when given the option not to respond, “I haven’t thought much about this,” most survey respondents answered anyway in research done by Manza and Uggen [106]. This finding, coupled with our measure of answer confidence, suggests that our questionnaire was able to capture participants’ actual level of information.

However, replications and extensions of the present study should strive to develop a more refined instrument comprising a greater number of dimensions of white-collar crime. The knowledge survey that was used only included ten items, which is far from providing an exhaustive review of a multifaceted construct like white-collar crime. A comprehensive scale therefore ought to comprise more examples of the various harms caused by white-collar crime, be they financial (e.g., price-gouging, price-fixing, insider trading, strategic bankruptcy, anti-trust violations, fraud, embezzlement, etc.), physical (e.g., workplace-related deaths and injuries, medical negligence and malpractice, endangerment of customers by the food and pharmaceutical industries, environmental pollution, etc.), or moral (e.g., destabilizing foreign nations through coups d’état, unlawful warfare and war profiteering, crimes of electioneering and usurpation of power, etc.).

Besides its admittedly unrefined measure of public knowledge about white-collar crime, the present study was further limited by its non-random sample. Although Mechanical Turk turned out to be an acceptable data collection method, the sample was not truly representative of the overall U.S. population and comprised a disproportionate number of relatively young and well-educated white citizens who were recruited from the Internet. It seems likely that college graduates would have had prior exposure to cases of white-collar crime because of the left-leaning academic agendas in many undergraduate courses. Replications with a larger, probability sample are therefore warranted.

Implications and avenues for future research

The main purpose of this paper was to detail the extent to which the public is knowledgeable about various dimensions of white-collar crime. It should be noted that two related studies using the same database (but only composite measures of knowledge) have already been published. The first one discussed the socio-demographic correlates of knowledge about white-collar crime [73]. More knowledgeable participants included Whites, those with higher education levels, without any religious affiliation, and who used the Internet as their main source of information. Conversely, less knowledgeable respondents and “’myth’ adherers” comprised men, those politically more conservative, Republicans, conservative Protestants, and subjects who relied on traditional (and therefore corporate-owned) media sources. These findings imply that the web might be used as an alternative educational platform to inform the public about white-collar crime.

The second study [107] investigated the consequences of knowledge about white-collar crime. Public awareness was associated with greater perceived seriousness of white-collar offenses and punitiveness toward their perpetrators. On the other hand, less knowledgeable participants exhibited more tolerance and leniency. What remains to be known is whether exposure to relevant information about white-collar crime would translate into more punitive sentiments or if “myth” adherence would hinder the effect of white-collar crime awareness programs.

We may expect the latter scenario for two reasons. First, it is possible that irrational emotions such as fear trump empirically based evidence in opinion formation. Research suggests that fear of crime is positively associated with punitive attitudes and support for “tough on crime” policies [38]. Crimes that the public perceives to be more physically harmful are expected to heighten such fear. Recall that a majority of subjects in this study underestimated the greater physical harmfulness of white-collar crime compared to street crime. Perhaps corporate violence (e.g., the calculated endangerment of workers, customers, and civilians) or state crime in other countries simply do not strike as much fear in them as offenses which they might perceive to be more direct, brutal, and likely to befall them (e.g., armed robbery, rape, murder, etc.). Consequently, their “myth” adherence may be the result of lower perceived risks of victimization rather than the denial of physically harmful white-collar crimes.

Second, information that incriminates big businesses might clash with right-leaning political ideology and religious orientation. As previously mentioned, increased demand for tougher sanctions against high-status offenders could hypothetically result from exposure to relevant information about the complex offenses in which the elite engage. Nevertheless, analogous to cognitive dissonance [108], “myth” adherence might lead business supporters to deny inconvenient truths relative to crimes of the powerful, which would then undermine the effect of increased awareness on prosecutorial efforts against white-collar crime. It is therefore crucial to gain a better understanding of the etiology and strength of these “myths” and of the manner in which they may influence public opinion about white-collar crime.


Readers may find this item ambiguous as religious leaders/organizations can actually engage in white-collar crime. Similarly, corporations can themselves be the victims of white-collar offenders. Nevertheless, we choose to remain faithful to Sutherland’s original definition, which clearly focused on the occupation of the perpetrators.


We chose not to use a larger monetary amount - one commonly observed in high-scale white-collar crime cases for instance - because it would not have been realistically applicable to street crime for comparison purposes.


Our decision to include medical crime was based on (1) pressure for profit in medical corporations increasing the frequency of malpractice, and (2) corporate negligence when a hospital fails to ensure professional competence among its employees. As such, we maintain that medical crime can be defined as white-collar crime.


This question was designed to assess if respondents were aware of the existence of human trafficking in developed countries; it was not intended to suggest that the prevalence of human trafficking is more prevalent in developed countries. Still, consistent with the white-collar crime construct, seemingly respectable corporations may connive with organized crime to obtain cheap workforce. In California, for example, the 2012 Business Transparency on Trafficking and Slavery Act requires companies to make public disclosures of their efforts to ensure that their supply chains are free from forced labor and human trafficking.


A reviewer noted that overcompliance is actually a current source of corporate rivalry. However, we still rely on years of green criminology research (see, e.g., Stretesky et al. [94]. The treadmill of crime: Political economy and green criminology. Routledge) to support our claim that, although admittedly better than it was, the trend for corporations and states alike (e.g., Florida) is far from being overly supportive of clean renewable energy.


It should be noted that these labels are used simply as conceptual devices to categorize/sort respondents. Readers should not infer from them that we are judging participants when they seemingly refuse to accept empirical facts.


A reviewer asked how many questions a subject had to answer correctly and with confidence to be labeled a “truth accepter” as opposed to a “lucky guesser.” We did not look at that. Moreover, the same subjects could accept some truths but deny others. This is definitely a question that future research will want to address.


Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of Criminology and Criminal JusticeUniversity of TampaTampaUSA
  2. 2.Department of CriminologyUniversity of South FloridaTampaUSA