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The ideal of a time-allocation study is a "god's-eye view" of everything everyone in the research population does. That this is completely unfeasible should not deflect us from recognizing that it is the ideal. When we compromise this ideal for practical reasons, we should do so reluctantly and self-reflectively, with the knowledge that too many compromises may result in collecting masses of misleading or useless data. In designing a time-allocation study, evaluation of alternative methods should incorporate the following four rules of thumb.

Coding Rules Must Be Explicit

At the present stage of research, when standards for describing human behaviour are neither rigorously developed nor widely shared, the best that researchers can hope for is to develop explicit descriptions of how they recorded particular behaviours and how they coded them into higher-order categories. Each study should, as a matter of course, produce a code-book that other researchers may obtain and use when comparing one study with another. Then it will not matter so much if one baseball-playing father is coded as "child-caretaking" while in another study such a father is coded as enjoying "recreation," because, by referring to the separate code-books for each study, comparative researchers can recode the behaviours to correspond.

This problem is among the most serious confronting time-allocation research. It was the single most time-consuming and difficult aspect of developing a standardized coding scheme for cross-cultural comparisons in the UCLA Time Allocation Project. In a coordinated field study, such as that of Gross and his co-workers in Central Brazil (1979), a team of researchers can achieve intercoder reliability through pre-field-work training. But such projects are rare, and the prevailing pattern of individualistic, and to a degree idiosyncratic, coding schemes means that some ambiguity in exactly how observed behaviour comes to be coded as this or that "activity" is inevitable whenever we are trying to interpret another researcher's time-allocation data.

For those responsible for making and implementing policy, this implies both a need for caution and an opportunity. Time-allocation data, being numerical, can be presented in decimal-point precision, but, given the limitations of data-collection techniques, must not be regarded as more than estimates of the general pattern of time allocation in a community. On the other hand, by designing their own time-allocation component into new research, planners can carefully define coding rules, train for intercoder reliability, and feel suitably confident of the accuracy of their findings (see, for example, Neumann and Bwibo, 1987). This is a case where careful planning well in advance of field research can pay large dividends in the quality of data obtained.

Samples Must Be Representative

One of the compromises with the god's-eye view ideal is that we can only observe or interview a fraction of the population a fraction of the time. Thus, all time-allocation research is done on samples. This means that the rules of statistical inference apply, and the basic requirement for representative sampling must be met. To the greatest possible extent, the individual subjects should be randomly drawn from the population, and the times for which their behaviour is recorded should be random moments drawn from the stream of time. When this is impossible, a researcher must pause and give careful thought to what is being lost in terms of the generalizability of the data, and should devise compensatory methods wherever possible. For example, Baksh and Paolisso (1986), in collecting a very large set of time-allocation observations among the Embu of Kenya, found that observing individuals at random throughout a large region of scattered homesteads was prohibitively costly in researchers' travel time. Instead, they devised a roundabout route through the territory that passed each homestead, and proceeded to move along that route making spot checks at each house along the way, resuming each day where the previous day's observations left off (a team of researchers took turns). Since each household visit involved certain unpredictable delays, the day's observations never ended at the same house, and over time an essentially random pattern of household visits resulted. This compromise allowed for a highly efficient use of researchers' time without seriously compromising representativeness.

Short-term Memory Is More Reliable than Long-term Memory

It has been demonstrated that reports of behaviour made immediately (within 2-3 minutes) after an observed event are much more accurate than reports made after several minutes have elapsed. when short-term memory retention gives way to the distortion of information in long-term memory, which is dominated by pattern-seeking. Thus, long-term memory conforms much more to "cognitive maps" of what behaviour should be like than does short-term memory. While fresh, it retains a fairly clear and objective image of what actually happened. These cognitive maps are partly cultural, so that long-term recall tends to conform to implicit, shared ethnocentric preconceptions, and partly personal, which may lead to the recollection of selected behaviours that confirm biases and support personal theories while failing to capture those that do not. It is especially important to keep in mind that this is done completely unconsciously. In fact, people are strongly inclined to doubt that they even do this, though the experimental evidence is overwhelming (Bernard et al., 1984).

Methodologically, this implies that direct observations will be most effective when the observer immediately records the behaviour as it happens. Similarly, for informant selfreports, greater accuracy will be achieved if the informant immediately records his or her behaviour. How to do this without totally disrupting the flow of behaviour will require some ingenuity. For example, researchers are beginning to experiment with beeper-type systems, whereby the subject is "beeped" at a random moment, and complies by quickly noting in a pocket notebook the time and a description of the activity in which he or she is engaged and then proceeding with the activity. This method, if it is successful, will combine some of the strongest features of both the direct observation and informant selfreport methods.

Direct Observation Generates Unexpected New Information

Researchers who specialize in direct observations rather than informant self-reports often comment on the serendipity of unexpected insights provided by the first-hand observation (Johnson, 1978b; Gillespie, 1979). Direct observation of behaviour on a random schedule forces the researcher out of routines, landing him or her in unexpected places at unexpected times. It enhances the participant observer aspect of the fieldwork, and generally strengthens and extends the field-worker's personal relations among the study population. It can help the investigator overcome some timidity or reluctance about being in certain situations, and, just as a picture is worth a thousand words, it gives the researcher the wealth of data and sense impressions which only direct apprehension of an event can provide, but which cannot be achieved by asking an informant to tell about it.


Time-allocation data are valuable means for describing the behaviour of people in the full range of their activities. Incorporated during the planning stages, studying time allocation in the proposed project area can provide a wide range of information for project development. Integrated into project implementation, it can help monitor changes as they occur. For example, are members of a targeted group increasing their participation in income-generating activities? All methods of time-allocation research, however, involve compromises with the ideal of obtaining complete and accurate information. Researchers must select from a variety of possible approaches those which achieve their specific research goals most fully.

It is important to maintain the clear distinction between methods based on direct observation by a trained researcher and those based on informant self-report. Direct observation tends to be expensive of a researcher's time and may be perceived as intrusive by the subjects, whereas informant self-reports depend on the documented frailty of human memory and may suffer greatly if informants are indifferent or secretly hostile to the research project and its personnel.

Four rules of thumb can help strengthen any time-allocation project: coding rules and categories must be made explicit and available to other researchers; observations must be representative of the population to which they will be generalized; observations recorded immediately after the event has occurred (short-term memory) are much more reliable than observations recorded more than a few minutes after the event (long-term memory); and direct observation of the event, by placing the researcher in the fullness of the context of behaviour, generates unexpected new data and insights beyond the mere quantitative description of time use.

Obviously, descriptions of patterns of time allocation can be useful in a wide variety of ways, complementing (not replacing) data on economic behaviour, household structure, socio-economic status, ethnicity, and so on. Perhaps the most significant limitation from the policy standpoint is that, like many essentially ethnographic methods, the data are most complete when collected over a period of at least a year, in a fairly small community. How can such a method be of use in a real world where a research team may have only two weeks to survey a region and develop policy recommendations?

In cases of extreme urgency, collection of valid time-allocation data is probably impractical. But, with some foresight, several possibilities suggest themselves on how to include such data in many projects. First, as mentioned above, if one time-allocation study can be done in a region, future short-term research projects can make inferences of time use based on that study. Such projects might include household surveys measuring useful predictors of time-use patterns (as established in the study). Second, in many world areas it is practical to train local researchers to conduct time-allocation studies over the long term; an expert team of researchers may actually need to visit the area only for a short period. If the study is done in advance of the team visit, the team can use the data to develop more precise questions and to formulate their recommendations.

Finally, even if time-allocation data are only collected over a short period, they can be very useful. True, we cannot use such data to construct a model of time use for an entire year. But they can give a rich picture of the daily round, of where and how people spend their time, and in whose company. Particularly when the preferred methods (spot checks, informant diaries, and 24-hour recall) are used, it is much better to have such data than not to have it, for it provides insights and opens avenues of inquiry that no other kinds of information can offer.


1. Support for this seven-year project, Standardized Cross-cultural Time Allocation Database, comes from National Science Foundation (NSF) grants BN84-19033 and BN87-04604.


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