Labor Requirement - Participatory Approach

Method of data collection and data needed to compute the method:

The scientists would need to focus on questions of labor relative to the ‘local’ or current technology.  Where the proposed or new technology is used, the questions would have to mainly focus on the amount of labor required to produce the output with the new technology and whether the farmers or adopter would find enough labor for the technology for that season.  An example of procedure to assess the labor requirements of new technology relative to the ‘local’ technology is to ask farmers about their perceptions:

1. Compared to the local technology, how would you rate the labor requirements of the new technology?
2. Does the new technology require more labor?
3. If so, what activity is the most labor demanding for the new technology?
4. Given the labor requirements, how would you rate the local technology versus the new technology?  

The rating of the technology may be done using the rating of labor requirements at: “high”, “intermediate”, or “low”.  Please note that ratings such as “very good”, “intermediate”, and “poor” may not be appropriate for this metric so attention should be made towards correct specifications of wording for rating.  Use of card charts that indicate the activities to where labor is demanded for the new technology is critical. Using these activity charts, participants may indicate labor requirements of the technologies.  It is recommended that the farmers are familiar with the proposed technology.  This may be done by educating them on the attributes of the technology beforehand, or choosing farmers that have experimented or observed the technology being used in the field.

Unit of analysis:

The unit of analysis is the average rating.  A high rating in this case will mean a high labor requirement and low rating, a low labor requirement.  Examining variation between groups of farmers by gender, wealth rankings, and other characteristics may be done depending on the method of data collection and size of the sample.  For example, if a focus groups is used to obtain data on labor requirements without recording results for each individual and their demographics (gender), then disaggregation may be difficult.  At the same time, if research can randomly sample farmers to obtain a representative population of farmers to participate in the participatory technology evaluation of labor, then statistical tests may be performed to assess if significant differences may exist across groups. 

Limitations regarding estimating and interpreting:

A limitation to this method may be the sample size and the questions that the researcher is trying to assess.  If the number of farmers is very small, it is very difficult to generalize the findings from this analysis.  This method requires, like most data collection approaches, proper training and understanding on the design of the survey questions, use of visualizations, and ensuring that the participants understanding on how to assess and answer the questions using aid such as card, stones, grains e.t.c.  Failure to do this might lead to spurious results (CIMMYT, 1988; Bellon, 2001).