What is PAR?



What is PAR and Why Is It Important?

By Lawrence Susskind*

It’s time for social scientists to stop pretending to be natural scientists and to acknowledge why applied social science research should be something else all together.[1] Natural scientists, employing the scientific method, can generate causal generalizations ("proofs") that can be counted on to apply reliably across time and place. Social scientists, on the other hand,  can only know something about very specific situations. Generalizations across people, organizations, communities, and countries are impossible to substantiate.. Furthermore, the statistical tools available to social scientists can only help us understand, not prove, why things happen. The differences between the social sciences and the natural sciences outweigh their commonalities, and efforts to "control" everything but the focus of a specific social scientific study are either unethical or bound to fail.

This is not to say that applied social science research isn't important. On the contrary, the most serious problems we face today are social and political, not physical. We need to make sure that social science is used to produce prescriptive insights and advice for those trying to promote social change.

Where have social scientists gone wrong?

There are some social scientists, particularly economists, who aspire to the mathematical rigor of the natural sciences in their research. They are committed to the ideal of "double blind" controlled experiments.  To prove the poverty-relieving effects of a specific policy or program they would apply that idea in half the community but not the other half, to see if there are statistical differences in outcomes over time. This troublesome for at least three reasons:

  1. First, you have to believe that the two halves of the community are initially the same (and stay the same) during the course of the experiment.
  2. Second, you must believe that everything else remains constant during the course of the experiment.
  3. Third, you have to believe that the experimental effort and not something else caused whatever statistically results emerged..

Putting aside ethical and moral concerns about withholding a benefit or imposing something bad on half a community so that someone’s theories can be tested, serious methodological problems remain. Mere correlation isn't a sufficient basis for reshaping public policy or interfering in people's lives. Even more important is the fact that statistical relevance doesn't explain why good or bad things happen. Social scientists should stop pretending that correlation equals causation. They should admit that the complexity and uncertainty involved in the social systems in which we live and work make science-like generalizations about people, communities and institutions extremely unreliable.




Getting social science back on track

In light of these concerns, social scientists should work harder to make connections to the “problem-having”clients, communities, agencies and governments they intend to help.  They should be working in collaboration with these groups to figure out what can be learned from past and current practices or events. Alliances of this sort, in which the community’s priorities and capacities guide any research endeavor, may seem less than ideal to scholars who want to frame their own research questions, use methods of analysis that peer-reviewers will approve, remain ‘objectively’ detached from the places or groups they study, and draw whatever conclusions make sense to them. Instead, I advocate a very different approach to applied social science called Participatory Acton Research (PAR).

PAR produces “actionable” knowledge by focusing on individual situations rather than on statistical analysis of large samples or controlled experiments. All PAR knowledge is "situated."  That means it is place- or case-specific. PAR puts a premium on local knowledge (what people in real situation know from their first-hand experience), rather than what experts think. And, PAR measures the success of applied social research in terms of the what client-communities understand , rather than what peer-reviewers think or the replicability of  findings. The goal of PAR-like applied social research isn't to generate proof.. On the contrary, the objective of PAR is to generate what Aristotle would have called "practical wisdom" or useable knowledge, believable to those who have to take action if social change is going to occur. Davydd Greenwood and Morten Levin, in Introduction to Action Research: Social Research for Social Change (2006), do a nice job of summarizing the development and current state of PAR.

Many dilemmas still surround participatory action research. These are the focus of ongoing debate among a growing community of PAR scholars and practitioners. Who represents a community, an agency or a client? How should power imbalances in a client-community be handled? How can a "friendly outsider" (i.e. a PAR researcher) convince a client-community that he or she should be trusted? Who should make the final decision about which data ought to be gathered and how findings should be interpreted? How should case specific findings be integrated with what has been learned from other cases or from insights generated by traditional applied social scientists? What role should PAR researchers play in formulating prescriptions for action? Can and should the PAR researcher stay involved with a client-community as its seeks to monitor results and make ongoing adjustments?

Building a community of PAR scholars

For the past two years, I have been co-teaching PAR seminars at MIT with my colleague Dayna Cunningham. In our academic department there has been an extended discussion of whether PhD candidates should be allowed to substitute these classes for more traditional qualitative research methods classes. From my standpoint, there are three reasons why PAR methods should be accepted as a viable alternative. First, unless graduate students learn how to interact with a client-community from the outset of a research effort, they will never learn how to communicate "with" rather than send messages "to" agencies, groups, organizations and institutions seeking to promote social change. Second, unless they learn how to make sense of what is happening in a specific case or context, rather than in a randomly drawn sample of places or situations, they will always be limited to analyzing superficial correlations and missing the deeper causal dynamics. Third, unless they learn how to build relationships with the users of actionable knowledge, they will be stuck offering pronouncements to the "cognoscenti" rather than collaborating with the people committed to making social change happen.

The resistance to PAR is strongest among social scientists who yearn to be part of the natural science fraternity, and who are more concerned about being respected by other academics than they are about building the capacity of client-communities to solve the problems they face. In their view, PAR advocates feed right into the hands of natural science skeptics who think putting "social" in front of scientist is equivalent to putting "witch" in front of "doctor." PAR practitioners, for their part, are worried that traditional social scientists are oblivious to the harm they do when they generalize about social and political phenomenon and fail to appreciate the case specific implications of their findings.

We want to initiate a different conversation. PAR teachers and practitioners should focus on explaining to their potential client-communities what they do, and why they do it (and why it would be best to work with PAR researchers rather than traditional social scientists). They should do more to codify the ethical norms that guide PAR in practice so they can be held accountable. And, they should think hard about the best ways of integrating what PAR teaches about case specific situations with the kinds of generalizations that traditional social scientists produce. Finally, we believe that graduate students interested in PAR should also seek to master a range of traditional science research methods. Mixed methods can yield valuable insights.


*Lawrence Susskind is Ford Professor of Urban and Environmental Planning in the Department of Urban Studies and Planning at MIT.  He has been a member of the MIT faculty for more than 40 years. He is also Vice-Chair of the Program on Negotiation at Harvard Law School and Founder/Chief Knowledge Officer of the Consensus Building Institute.


[1] A number of authors have done a masterful job spelling out all the reasons why social scientists should stop aspiring to be natural scientists. See Bent Flyvbjerg’s books Real Social Science (2012) and Making Social Science Matter (2001) for a full explanation.