Campbell's Law

Original statement and context

Campbell's law was set out by American social psychologist and methodologist Donald T. Campbell in a 1976 Dartmouth College paper, "Assessing the Impact of Planned Social Change" (published in a journal in 1979). It reads: "The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor." Campbell, a pioneer of program evaluation and quasi-experimental design, warned that measuring policy effects itself changes the behavior of those targeted. He gave the example that when test scores are used as indicators of educational achievement, teachers teach to the test rather than general competence, and scores lose their meaning. This shows that measurement validity cannot be separated from how measures are used socially.

Relation to Goodhart's law

Economist Charles Goodhart (1975) observed that when a monetary aggregate is made a control target, its statistical relationships with other variables break down, and anthropologist Marilyn Strathern (1997) generalized this as "when a measure becomes a target, it ceases to be a good measure." Whereas Goodhart's law focuses mainly on the loss of an indicator's signal value, Campbell's law stresses that using indicators "corrupts" the actual social process, changing the behavior and institutions being measured. Both share concerns with the Lucas critique in economic policy. Steven Kerr's (1975) "folly of rewarding A, while hoping for B" belongs to the same line, and Holmström and Milgrom (1991) theorized it with a multitask agency model in which rewarding only measurable tasks reduces effort on hard-to-measure ones.

Cases and remedies

Education is the classic case. Jacob and Levitt (2003) showed statistically that teacher cheating on answer sheets rose in Chicago public schools once test results were used to evaluate schools, and Koretz (2008) documented "score inflation" in which high-stakes scores rose while low-stakes scores did not; Nichols and Berliner (2007) called this "collateral damage." In policing, Eterno and Silverman (2012) reported downgrading of crime classifications under New York's CompStat system, and in health care Bevan and Hood (2006) analyzed "gaming" around targets such as England's four-hour emergency standard. Espeland and Sauder (2007) analyzed the "reactivity" by which university rankings change schools' behavior. Proposed remedies include using multiple indicators, combining them with qualitative judgment, rotating or auditing measures, and using indicators for learning rather than rewards. Jerry Muller's The Tyranny of Metrics (2018) surveys the costs of metric fixation, and the law is an important warning in KPI design.

FAQ

How does Campbell's law differ from Goodhart's law?

Both say targeting an indicator causes problems, but Goodhart's law focuses on the collapse of the indicator's information value, while Campbell's law emphasizes that indicator use distorts real social processes and behavior.

What are typical examples of Campbell's law?

Teaching to the test and answer-sheet cheating after test scores were used to judge schools and teachers, and downgrading of crime reports after crime statistics became performance targets.

Sources reviewed: 2026-10-26

References

1. Campbell, D. T. (1976). Assessing the impact of planned social change. Occasional Paper Series #8. Hanover, NH: Public Affairs Center, Dartmouth College.
2. Campbell, D. T. (1979). Assessing the impact of planned social change. Evaluation and Program Planning, 2(1), 67–90.
3. Goodhart, C. A. E. (1975). Problems of monetary management: The U.K. experience. Papers in Monetary Economics, Reserve Bank of Australia.
4. Strathern, M. (1997). 'Improving ratings': Audit in the British university system. European Review, 5(3), 305–321.
5. Kerr, S. (1975). On the folly of rewarding A, while hoping for B. Academy of Management Journal, 18(4), 769–783.
6. Jacob, B. A., & Levitt, S. D. (2003). Rotten apples: An investigation of the prevalence and predictors of teacher cheating. Quarterly Journal of Economics, 118(3), 843–877.
7. Koretz, D. (2008). Measuring Up: What Educational Testing Really Tells Us. Cambridge, MA: Harvard University Press.
8. Bevan, G., & Hood, C. (2006). What's measured is what matters: Targets and gaming in the English public health care system. Public Administration, 84(3), 517–538.
9. Nichols, S. L., & Berliner, D. C. (2007). Collateral Damage: How High-Stakes Testing Corrupts America's Schools. Cambridge, MA: Harvard Education Press.
10. Holmström, B., & Milgrom, P. (1991). Multitask principal–agent analyses: Incentive contracts, asset ownership, and job design. Journal of Law, Economics, & Organization, 7, 24–52.
11. Muller, J. Z. (2018). The Tyranny of Metrics. Princeton, NJ: Princeton University Press.
12. Eterno, J. A., & Silverman, E. B. (2012). The Crime Numbers Game: Management by Manipulation. Boca Raton, FL: CRC Press.
13. Espeland, W. N., & Sauder, M. (2007). Rankings and reactivity: How public measures recreate social worlds. American Journal of Sociology, 113(1), 1–40.