Systemic bias

Systemic bias, also called institutional bias, is the inherent tendency of a process to support particular outcomes. The term generally refers to human systems such as institutions; the equivalent bias in non-human systems (such as measurement instruments or mathematical models used to estimate physical quantities) is often called systematic bias, and leads to systematic error in measurements or estimates. The issues of systemic bias are dealt with extensively in the field of industrial organization economics.

In human institutions

Cognitive bias is inherent in the experiences, loyalties, and relationships of people in their daily lives, and new biases are constantly being discovered and addressed on both an ethical and political level. For example, the goal of affirmative action in the United States is to counter biases concerning gender, race, and ethnicity, by opening up institutional participation to people with a wider range of backgrounds, and hence a wider range of points of view. In India, the system of scheduled castes and tribes intends to address systemic bias caused by the controversial caste system, a system centered on organized discrimination based upon one's ancestry, not unlike the system that affirmative action aims to counter. Both the scheduling system and affirmative action mandate the hiring of citizens from within designated groups. However, without sufficient restrictions based upon the actual socio-economic standing of the recipients of the aid provided, these types of system can, and allegedly do, result in the unintentional institutionalization of a reversed form of the same systemic bias,^[1] which works against the goal of rendering institutional participation open to people with a wider range of backgrounds. It can therefore be argued that all human institutions can do is to minimize bias as much as possible, and utilize education to increase awareness of it wherever possible.

Major causes

The study of systemic bias as part of the field titled organizational behavior in industrial organization economics is studied in several principle modalities in both non-profit and for-profit institutions. The issue of concern is that patterns of behavior may develop within large institutions which become harmful to the productivity and viability of the larger institutions from which they develop. The three major categories of study for maladaptive organizational behavior and systemic bias are counterproductive work behavior, human resource mistreatment, and the amelioration of stress-inducing behavior.

Counterproductive work behavior

Counterproductive work behavior, or CWB, consists of behavior by employees that harms or intends to harm organizations and people in organizations.^[2]

Mistreatment of human resources

There are several types of mistreatment that employees endure in organizations.

Abusive supervision

Abusive supervision is the extent to which a supervisor engages in a pattern of behavior that harms subordinates.^[3]

Bullying

Although definitions of bullying vary, it involves a repeated pattern of harmful behaviors directed towards an individual.^[4]

Incivility

Incivility consists of low-intensity discourteous and rude behavior with ambiguous intent to harm that violates norms for appropriate behavior in the workplace.^[5]

Sexual harassment

Sexual harassment is behavior that denigrates or mistreats an individual due to his or her gender, creates an offensive workplace, and interferes with an individual being able to do their job.^[6]

Stress

Occupational stress concerns the imbalance between the demands (aspects of the job that require mental or physical effort) and resources that help cope with these demands.^[7]

Examples

Financial Week reported May 5, 2008 (emphasis added):

But we travel in a world with a systemic bias to optimism that typically chooses to avoid the topic of the impending bursting of investment bubbles. Collectively, this is done for career or business reasons. As discussed many times in the investment business, pessimism or realism in the face of probable trouble is just plain bad for business and bad for careers. What I am only slowly realizing, though, is how similar the career risk appears to be for the Fed. It doesn't want to move against bubbles because Congress and business do not like it and show their dislike in unmistakable terms. Even Federal reserve chairmen get bullied and have their faces slapped if they stick to their guns, which will, not surprisingly, be rare since everyone values his career or does not want to be replaced à la Volcker. So, be as optimistic as possible, be nice to everyone, bail everyone out and hope for the best. If all goes well, after all, you will have a lot of grateful bailees who will happily hire you for $300,000 a pop.^[8]

Versus systematic bias

The difference between the words systemic and systematic is somewhat ambiguous.

"Systemic bias" and the older, more common expression "systematic bias" are often used to refer to the same thing; some users^[who?] seek to draw a distinction between them^[why?], suggesting that systemic bias is most frequently associated with human systems, and related to favoritism.^{[citation needed]}

In engineering and computational mechanics, the word bias is sometimes used as a synonym of systematic error. In this case, the bias is referred to the result of a measurement or computation, rather than to the measurement instrument or computational method.^[9]

Some authors try to draw a distinction between systemic and systematic corresponding to that between unplanned and planned, or to that between arising from the characteristics of a system and from an individual flaw. In a less formal sense, systemic biases are sometimes said to arise from the nature of the interworkings of the system, whereas systematic biases stem from a concerted effort to favor certain outcomes. Consider the difference between affirmative action (systematic) compared to racism and caste (systemic).^{[citation needed]}

References

^ Jaroff, Leon et al. (April 4, 1994) "Teaching Reverse Racism", Time Magazine
^ Spector, P. E., & Fox, S. (2005). The Stressor-Emotion Model of Counterproductive Work Behavior Counterproductive work behavior: Investigations of actors and targets (pp. 151-174). Washington, DC: American Psychological Association; US.
^ Tepper, B. J. (2000). "Consequences of abusive supervision". Academy of Management Journal. 43 (2): 178–190. doi:10.2307/1556375.
^ Rayner, C., & Keashly, L. (2005). Bullying at Work: A Perspective From Britain and North America. In S. Fox & P. E. Spector (Eds.), Counterproductive work behavior: Investigations of actors and targets. (pp. 271-296). Washington, DC, US: American Psychological Association.
^ Andersson, L. M.; Pearson, C. M. (1999). "Tit for tat? The spiraling effect of incivility in the workplace". Academy of Management Review. 74: 452–471. doi:10.5465/amr.1999.2202131.
^ Rospenda, K. M., & Richman, J. A. (2005). Harassment and discrimination. In J. Barling, E. K. Kelloway & M. R. Frone (Eds.), Handbook of work stress (pp. 149-188). Thousand Oaks, CA: Sage.
^ Demerouti, E.; Bakker, A. B.; Nachreiner, F.; Schaufeli, W. B. (2001). "The job demands-resources model of burnout". Journal of Applied Psychology. 86 (3): 499–512. doi:10.1037/0021-9010.86.3.499.
^ "Paging Paul Volcker. The former Fed chairman was tougher and less eager to please than his successor, Alan Greenspan", Jeremy Grantham, Financial Week, 5 May 2008
^ John Robert Taylor (1999). An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements. University Science Books. p. 94, §4.1. ISBN 0-935702-75-X.

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v t e Biases
Cognitive biases	Acquiescence Ambiguity Affinity Anchoring Attentional Attribution Actor–observer Correspondence Authority Automation Availability Mean world Belief Blind spot Choice-supportive Commitment Confirmation Selective perception Compassion fade Congruence Cultural Declinism Distinction Dunning–Kruger Egocentric Curse of knowledge Emotional Extrinsic incentives Fading affect Framing Frequency Frog pond effect Halo effect Hindsight Horn effect Hostile attribution Impact Implicit In-group Intentionality Illusion of transparency Mean world syndrome Mere-exposure effect Narrative Negativity Normalcy Omission Optimism Out-group homogeneity Outcome Overton window Precision Present Pro-innovation Proximity Response Restraint Self-serving Social comparison Social influence bias Spotlight Status quo Substitution Time-saving Trait ascription Turkey illusion von Restorff effect Zero-risk In animals
Statistical biases	Estimator Forecast Healthy user Information Psychological Lead time Length time Non-response Observer Omitted-variable Participation Recall Sampling Selection Self-selection Social desirability Spectrum Survivorship Systematic error Systemic Verification Wet
Other biases	Academic Basking in reflected glory Déformation professionnelle Funding FUTON Inductive Infrastructure Inherent In education Liking gap Media False balance Vietnam War Norway South Asia Sweden United States Arab–Israeli conflict Ukraine Net Political bias Publication Reporting White hat
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