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Once established in traditional societies, recipes are communicated by interpersonal teaching and learning strategies, and maintained by the practitioners of technologi-cal traditions. Modern industrial societies have available many more modes of knowledge transmission, from apprenticeship to computer simulations, most of which involve artifacts. Recipes are materialized today in nearly every print and electronic medium.
Manufacture recipes in all societies may include rituals because of the belief that such performances are needed. People thus carry out the interactions, confi dent that the ritual will help to create the product ( Malinowski 1954 ). Thus, some Sumerian glass recipes called for sacrifi cing a sheep and burning incense (e.g., Oppenheim et al. 1970 :44). Together, technical performances based on scientifi c knowledge and rituals buttressed by beliefs in “non-immediate sources of power, authority, and value” (Bell 1997 , xi) together yield tangible outcomes—e.g., the smelting of iron in an African village (Childs and Killick 1993 ) or the construction of a canoe for deep-sea voyages in Melanesia (Malinowski 1961 ). The “non-immediate sources of power, authority, and value” may be propitiated, placated, appealed to, avoided, obeyed, resisted, or merely referenced in rituals that alternate with or accompany technical performances.
Our models of recipes tend to lack rituals, which may leave scant archaeological traces. By drawing on ethnographic evidence and generalizations, however, we may be able to infer rituals that probably took place. Following Malinowski (1954) , for example, we should expect rituals to occur when specifi c interactions are risky to participants, very diffi cult to perform, or have uncertain outcomes. The Sumerian glass-making rituals predictably occurred prior to the failure-prone fi nal melt (cf.
Fischer 2008 ).
Why do recipes usually yield the expected product? The answer is that beneath the sequence of visible interactions, activities, and intermediate outcomes lies an invisible realm of empirical generalizations and experimental laws. Thus, a recipe’s interactions are in accord with, indeed depend upon, the validity of other nuggets of scientifi c knowledge. Asking how any recipe works its magic, then, leads directly to the exploration of this hidden realm, to research projects that bring to light the implicit generalizations. It is precisely these underlying generalizations that make it possible for a recipe, when followed skillfully, to create something entirely new to human experience—and to the universe.
People in every society invent recipes by acquiring the relevant generalizations, usually through trial and error. Let us envision a person developing a clay cooking pot for use over an open fi re. His or her fi rst attempts are likely to fail, but each failure leads to a change in technical choices, and eventually the aspiring potter may devise a successful recipe, perhaps one incorporating rituals. We may approximate this learning process by following the pot’s behavioral chain, positing the necessary generalizations, as in the following (see Schiffer and Skibo 1997 ):
1. If the potter chooses a local raw material containing enough clay to be workable, then a vessel can be formed.
2. If the potter in creating the paste adds enough nonclay particles to the clay, such as animal dung or sand, then the vessel is likely to dry without cracking.
Generalizations
3. If the vessel’s paste contains ample nonclay particles and the potter dries the vessel thoroughly, then it is likely to survive fi ring. 2
4. If the potter fi res the vessel at a suffi ciently high temperature, then it will have adequate strength and maintain its integrity during use.
5. If the potter treats the vessel’s interior surface to make it somewhat imperme-able, then it will heat its liquid contents effectively.
6. If the potter makes a globular vessel with walls of even thickness, and has added enough nonclay particles to the paste, then it will survive repeated heating/cool-ing episodes durheating/cool-ing use.
The appropriate raw clay and nonclay particles, once identifi ed, can be specifi ed as empirical generalizations. In many societies fi ring sometimes fails to produce the expected result, and so fi ring is often preceded by a ritual. As the recipe is developed and put into practice, the potter acquires the necessary skills.
Once the making of cooking pots became routinized as recipes perpetuated in a technological tradition, there was no need for experimental laws and empirical gen-eralizations to be explicit. They were likely to “surface only during times of experi-mentation (if at all)” (Schiffer and Skibo 1987 :597). Indeed, practitioners in traditional societies seldom supply generalizations when answering questions about why they engage in certain interactions. Often the response is simply, “that’s the way we’ve always done it.” A conversation-stopper, this answer invites the archae-ologist to model the underlying generalizations. The modeling process requires a sophisticated understanding of the technology, as gained through experiment (see the chapter “Contributions of Experimental Archaeology”), inference from behav-ioral observations, archaeometric studies (see “Contributions of Archaeometry”), experience as a practitioner, or studying modern scientifi c and engineering texts.
Even in industrial societies modeling is often necessary because practitioners—
from bakers to air conditioner technicians—merely follow long-standing recipes.
Modeling a recipe may suffi ce for some archaeological projects, but sometimes our research interests will also lead us to uncover the implicit generalizations.
The pottery example supports the claim that a recipe’s interactions are underlain by generalizations, which render their consequences somewhat probable. It follows that there is no rigid boundary between the content of a complex experimental law and that of a very simple recipe. As noted above, several experimental laws describe hard-hammer percussion, but that process also conforms to a recipe in which those experimental laws are implicit. I emphasize, however, that recipes are essential for modeling longer and more complex interaction and activity sequences .
Different recipes may result in a similar product (an instance of equifi nality).
Thus, by following any of several recipes, a potter may form vessels having similar formal properties and performance characteristics. And, in the replications of Folsom points, experiments have shown that many techniques can produce the char-acteristic channel fl akes (see chapter “Contributions of Experimental Archaeology”).
2 There are exceptions: some natural clays already contain suffi cient nonclay particles to permit successful drying, fi ring, and repeated use over a fi re.
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Archaeologists and historians have long known that new technologies have sometimes given rise to new science (e.g., Staudenmaier 1985 ). But my claim is stronger: new scientifi c knowledge—e.g., the recipe for how to make or use some-thing—is a necessary consequence of all technological development (see “Science:
A Behavioral Perspective”).
Discussion
Some readers may be surprised that I include recipes as a kind of scientifi c general-ization. After all, recipes for making a cooking pot or pumpkin pie connote mun-dane activities accessible to almost anyone. Yet, Robert Boyle, chief exponent of experimental methods in early modern science, “sought to acquaint himself with the practical procedures employed by tradesmen and artisans in their manipulations of nature” (Sargent 1994 :67; see also Hall 1956 :218–222, 308–309). Boyle’s familiar-ity with the activities of ordinary people—instead of immersion in tracts authored by ancient philosophers—was salutary because, he argued, “the ‘phenomena afforded by trades’ must be made a ‘part of the history of nature,’ because they may
‘both challenge the naturalist’s curiosity, and add to his knowledge’” (Boyle, quoted in Sargent 1994 :67). From tradesmen and artisans, Boyle learned recipes for mak-ing thmak-ings as well as the properties of materials—the kinds of knowledge that were integral to his natural philosophy.
In addition to Boyle’s historical precedent, there are other grounds for arguing that recipes are a kind of scientifi c generalization. First, we may model recipes as a complex expression compounded of both empirical generalizations and experi-mental laws. Let us represent the simplest possible recipe as “if X , then Y ,” where any X is an interaction among specifi c ingredients and tools, and Y is that interac-tion’s product. By itself, this statement is equivalent to an empirical generaliza-tion or experimental law. By expanding this expression, we may represent the steps of any recipe of greater complexity. To wit, if X 1 , then Y 1 ; if X 2 , then Y 2 ;….
if X n , then Y n (inspired by a discussion in Gooding 1990b:113). Thus, a recipe may be considered the shorthand expression of a compound and very complex generalization.
Second, recipes—and recipes alone—permit people to create, and researchers to explain , an emergent empirical phenomenon (the outcome). An important implica-tion is that, by knowing only ingredients, tools, and relevant generalizaimplica-tions, we would be unable to anticipate or explain the outcome, for the latter is determined by a recipe’s interaction sequences .
And third, the main function of scientifi c knowledge, as defi ned behaviorally, is that it empowers people to engage competently with the material world. Recipes meet this criterion especially well because they make possible the interaction sequences of behavioral chains, from processes of material procurement to cultural deposition.
Generalizations