Since this is new venture, we need to establish conventions. Since JASSS has been running since 1998 (twenty years!) it is reasonable to argue that something un-cited in JASSS throughout that period has effectively been forgotten by the ABM community. This contribution by Grémy is actually a single chapter in a book otherwise by Boudon (a bibliographical oddity that may have contributed to its neglect. Grémy also appears to have published mostly in French, which may also have had an effect. An English summary of his contribution to simulation might be another useful item for RofASSS.) Boudon gets 6 hits on the JASSS search engine (as of 31.05.18), none of which mention simulation and Gremy gets no hits (as does Grémy: unfortunately it is hard to tell how online search engines “cope with” accents and thus whether this is a “real” result).
Since this book is still readily available as a mass-market paperback, I will not reprise the argument of the simulation here (and its limitations relative to existing ABM methodology could be a future RofASSS contribution). Nonetheless, even approximately empirical modelling in the mid-seventies is worthy of note and the article is early to say other important things (for example about simulation being able to avoid “technical assumptions” – made for solubility rather than realism).
The point of this contribution is to draw attention to an argument that I have only heard twice (and only found once in print) namely that we should look at the form of real data as an initial justification for using ABM at all (please correct me if there are earlier or better examples). Grémy (1974, p. 210) makes the point that initial incongruities between the attitudes that people hold (altruistic versus selfish) and their career choices (counsellor versus corporate raider) can be resolved in either direction as time passes (he knows this because Boudon analysed some data collected by Rosenberg at two points from US university students) as well as remaining unresolved and, as such, cannot readily be explained by some sort of “statistical trend” (that people become more selfish as they get older or more altruistic as they become more educated). He thus hypothesises (reasonably it seems to me) that the data requires a model of some sort of dynamic interaction process that Grémy then simulates, paying some attention to their survey results both in constraining the model and analysing its behaviour.
This seems to me an important methodological practice to rescue from neglect. (It is widely recognised anecdotally that people tend to use the research methods they know and like rather than the ones that are suitable.) Elsewhere (Chattoe-Brown 2014), inspired by this argument, I have shown how even casually accessed attitude change data really looks nothing like the output of the (very popular) Zaller-Deffuant model of opinion change (very roughly, 228 hits in JASSS for Deffuant, 8 for Zaller and 9 for Zaller-Deffuant though hyphens sometimes produce unreliable results for online search engines too.) The attitude of the ABM community to data seems to be rather uncomfortable. Perhaps support in theory and neglect in practice would sum it up (Angus and Hassani-Mahmooei 2015, Table 5 in section 4.5). But if our models can’t even “pass first base” with existing real data (let alone be calibrated and validated) should we be too surprised if what seems plausible to us does not seem plausible to social scientists in substantive domains (and thus diminishes their interest in ABM as a “real method?”) Even if others in the ABM community disagree with my emphasis on data (and I know that they do) I think this is a matter that should be properly debated rather than just left floating about in coffee rooms (as such this is what we intend RofASSS to facilitate). As W. C. Fields is reputed to have said (though actually the phrase appears to have been common currency), we would wish to avoid ABM being just “Another good story ruined by an eyewitness”.
Angus, Simon D. and Hassani-Mahmooei, Behrooz (2015) ‘“Anarchy” Reigns: A Quantitative Analysis of Agent-Based Modelling Publication Practices in JASSS, 2001-2012’, Journal of Artificial Societies and Social Simulation, 18(4):16.
Chattoe-Brown, Edmund (2014) ‘Using Agent Based Modelling to Integrate Data on Attitude Change’, Sociological Research Online, 19(1):16.
Gremy, Jean-Paul (1974) ‘Simulation Techniques’, in Boudon, Raymond, The Logic of Sociological Explanation (Harmondsworth: Penguin), chapter 11:209-227.
Chattoe-Brown, E. (2018) A Forgotten Contribution: Jean-Paul Grémy’s Empirically Informed Simulation of Emerging Attitude/Career Choice Congruence (1974). Review of Artificial Societies and Social Simulation, 1st June 2018. https://rofasss.org/2018/06/01/ecb/