collier 2, stadistical models

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Statistical Models and Causal Inference: A Dialogue with the Social Sciences by DavidFreedman; David Collier; Jasjeet Sekhon; Philip StarkReview by: Jacob FelsonContemporary Sociology, Vol. 40, No. 1 (January 2011), pp. 30-31Published by: American Sociological AssociationStable URL: http://www.jstor.org/stable/25762936 .

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Reviews 31lifesavingmedical discoveries, social scienceexamples would resonate more with socialscientist readers. Medical examples are alsonot particularly helpful for social scientistsbecause causes in the social world do notusually operate likeviruses and vitamin deficiencies in thebody. Diseases and syndromesaremuch more predictable and less contingent than social causes. Freedman's discussion ofmedical discoveries is interesting foritsown sake, but not as useful as a demonstrationofhow social scientific research could orshould be done. Itwould have been moreuseful to see examples of compelling socialresearch, and to see the role (ifany) playedby statisticalmodeling.Quantitative researchers who are sympathetic to Freedman's perspective and arelooking for detailed guidebooks about howto proceed should look elsewhere. Thoseinterested in a more circumspect approachto quantitative analysis might profitmorefrom reading Richard Berk's (2003) bookabout regression modeling, Freese's (2006)proposal for replication standards, andYoung's (2009) paper about how to avoidunderestimating the uncertainty in modelspecifications.Butmany of theways inwhich causes arefound cannot be distilled to theiressence, systematized, and categorized in a separate fieldcalled methods. Instead, themeans of discovery are often unique to the problem athand. Freedman, the statistician, is abdicatingthe throne that quantitative researchersmayunwittingly have built forhim. As Learner(1983)wrote, methodology, like sex, isbetterdemonstrated than discussed, though oftenbetter anticipated than experienced. Canone thinkof amajor social scientificquestionthathas been resolved primarily through theuse of statisticalmodels? This is thequestionFreedman's book implicitlyasks. For his supporters, the question is rhetorical. For hisdetractors, the answer to the question wouldbe their first ine of defense.

ReferencesBeck, Richard. 2003. Regression Analysis: A Constructive Critique. Thousand Oaks, CA: SagePublications.

Firebaugh, Glenn. 2008. Seven Rules for SocialResearch. Princeton, NJ: Princeton UniversityPress.Freese, Jeremy. 2007. Reproducibility StandardsinQuantitative Social Science: Why Not Sociology? SociologicalMethods and Research36:153-172.Learner, Edward. 1983. Let's Take the Con Out of

Econometrics. American Economic Review.73:31-43.

Young, Cristobal. 2009. Model Uncertainty inSociological Research: An Application to Religion and Economic Growth. American Sociological Review. 74:380-97.

Codes of theUnderworld:How Criminals Communicate, by Diego Gambetta. Princeton,NJ: Princeton University Press, 2009. 336pp.$35.00 cloth. ISBN: 9780691119373.JanaArsovskaJohnJayCollege ofCriminal [email protected] Gambetta's innovative book Codesof theUnderworld: How Criminals Communicate has a lot to say about signaling, trustand semiotics. By combining theory withempirical findings,Gambetta illustrates thedilemmas criminals face as they strugglewith the problems of whom to trust,howtomake themselves trusted, and how tomaintain secrecy. Criminals want to signaluntrustworthiness, namely that they arecrooks. For thepurpose ofworking with other criminals, they also wish to signal thatthey are reliable. This need fordual signaling makes underworld communicationa remarkable case study. As Gambettarightly claims: [0]ne wonders how criminals evermanage to do anything together(p. 32).Gambetta's task inCodes of theUnderworldis to decode how criminals signal to eachother.When identifying partners, criminalscan miss opportunities, failing to seethrough thedisguises thatpotential partnersadopt. They may also mistakenly approachundercover agents. Miscommunication cantherefore be costly. Codes of theUnderworldanalyzes the techniques of dealing withinformationunder conditions ofuncertainty.It captures the reader's attention by raising

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collier 2, stadistical models

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