5. Guidelines on suggestions for incorporating gender issues into socio-economic methodologies
Secondary data used for sectoral planning are often derived from sources such as statistics, surveys and censuses, How these data reflect women's economic contribution is important and will influence development planning.
1. Labour statistics often undervalue women's contribution. The bulk of women's production takes place in the informal and non-monetary sectors which are not included in most national statistics.
Moreover, labour force calculations often define a woman as two-thirds of a man-equivalent and a child as one-third. The result of this manipulation of statistics is that the work done by women and children is reduced to a fraction of a "man-unit". New calculations, using full units for both sexes, must be made by planners and their effects on sector plans demonstrated.
Care should thus be taken when using labour statistics to indicate the contribution and availability of male and female labour. Review of other secondary sources or a special study may be needed to obtain a clear picture on labour availability by sex and season.
2. Population censuses are often conducted during slack periods of agricultural/fishing activity using short reference periods. Therefore, they are likely to omit persons such as migrants and women, who may be active during peak agricultural/rishing seasons, from the economically active population.
3. Numbers of female-headed households are not necessarily a good criterion for target group selection. Some types of female-headed households are likely to have less access to resources. On the other hand, they may be sole decision-makers -- this gives them more flexibility in deciding on allocation and use of resources. Information on female-headed households should he interpreted in conjunction with other data such as income levels, economic activities and household decision making.
4. Fishery statistics are biased towards the harvesting sub-sector. Frame surveys cover fishing units, gears, number of boats, crews, etc. but not processing and trading units. Consequently, information on women involved in the sector is hard to obtain. Sample surveys could be designed on the basis of frame surveys, which take note of the activities of processors and traders.
5. Subsistence production in rural and fishing areas, as well as domestic work, is unpaid and therefore often little valued by statisticians. Thus without taking into account the extent of the informal economy, planners are often inclined to the development of the formal market economy. Generally speaking, men participate more actively in the formal economy than women do. Analysis of other secondary sources, such as labour allocation studies may reveal the relative importance of different formal and informal market activities undertaken by men and women. When no information is available, a special study may have to be carried out on the roles and significance of the subsistence and market sectors.
6. Anthropometric measurements and health and nutrition indicators do not themselves reveal the causes of malnutrition and should therefore be analyzed in combination with other information, such as food availability, intra-household distribution of food, sanitary conditions, health status, etc. Moreover, protein energy malnutrition cannot be solved by increased supply of fish alone, but often requires other interventions such as increasing energy intake and the general improvement of health and sanitation.
7. Enumerators often confine their attention to male household members. Where information is given only by the men of the household, the census might understate the participation of women in economic activities. Data from such censuses should he supplemented with other information from special studies and secondary sources to provide a full picture of household activities.
8. Cost-benefit analyses to assist decision-making on development projects and programs is sometimes concerned only with total costs and total benefits and disregard the distribution of these benefits. For example, an analysis involving 'man-units' might obscure the importance of women to total labour inputs. The reduction of women to a fraction of a man-unit could mean that a project involving more men than women would be given higher ranking than an equivalent or better project involving more women than men.
An alternative is to separately show the costs and benefits of a given set of projects to different groups in society, and let the policy-makers decide on the relative weights to be given to each.
9. Government budgets and past expenditures are not necessarily a good indicator of commitment to gender issues. Often money is spent on buildings or equipment rather than on activities. Therefore, it is necessary to supplement these data with information from progress and annual reports of field staff or to interview key informants for details on activities.
Although the various methodologies used to generate socio-economic and socio-cultural data are qualitatively different (e.g. surveys, PRA, case studies), many contain a 'field work' stage. The design of the field work ascertains whether the data collected will be disaggregated by gender. Furthermore, the perceptions and attitudes of the persons conducting the field work are important. They need to have some knowledge of the local socio-cultural situation and a general understanding of gender issues in order to interpret the answers correctly. Several considerations, which apply to all methodologies, must be taken into account when planning and conducting field work.
1. Seasonal fluctuations in many fisheries activities have implications for field work. When carried out once (e.g. during one season of the year), it will not reach all men and women engaged in fisheries and fisheries related activities, especially if seasonal migration is high. To address this problem it is suggested that:
* Long recall periods extending over the entire year should be used as the reference period (although the accuracy of the data decreases with a longer recall period), or
* If resources permit, collect data several times at different times of the year, or
* If resources do not permit field work to be carried out during different seasons, interview key informants about the activities of the categories of people not present.
2. Questions on women's activities should be put to women rather than men, as they are likely to omit activities. Even when women are interviewed directly, a precise description of the information solicited is needed. If not, women themselves may under-report their activities (e.g. reproductive activities).
3. In order to reach as many men and women as possible during field work, it is important that: both their time schedules are taken into account when planning the interviews; and the interview is conducted in the language of common use.
4. Since a household is not a homogeneous undifferentiated grouping of people with shared and equal access to resources for and benefits from production, it is often necessary to take individuals rather than the household as enumeration units. Whereas data obtained from two or more individuals could probably be combined, there is no way of dividing up household data such as income and expenditure or activities to correspond to individual holdings from household members.
Comparison of information (e.g. access to resources, seasonal calendars) obtained from husband and wife or groups of men and women belonging to the same community, will reveal gender differences. Moreover, a discussion of the differences in views and perceptions between men and women may lead to proposals for solutions. This could thus be used as an important tool in gender-sensitive planning.
Collected information has to be aggregated in some way to enable sectoral planning and project formulation. There are various ways to aggregate information, but the reliability of these methods depends on the compatibility of definitions for data collected with different methods. For example, two surveys based on the household as the enumeration unit may use different definitions of the household, making comparison and aggregation of data difficult.
Aggregation of data can be based on fairly simple statistical aggregation methods such as frequency distribution, or more sophisticated social cost-benefit analysis (SCBA) and Geographical Information Systems (GIS).
SCBA is a system designed to ensure that all relevant factors are taken into account to enable decision makers to analyse the costs and benefits of different strategies to achieve set objectives. It allows for weighting of information relating to key issues such as income distribution between sex and class within a community. This means that if gender issues are considered important by decision-makers, weights could be accorded to ensure their relevance when a decision is taken. Thus, a scale of importance of various gender issues needs to be developed so that weights can be accorded each issue when performing a SCBA. This could be an objective scale to consider different aspects of gender, it could be a relative scale which views these aspects in relation to other factors in the appraisal process.
GIS allows the interpreter to identify the geographical distribution of various characteristics of the sector and at different levels. This can apply to natural resources, market mechanisms, household composition or any other type or combination of variables. Mapping this can then assist decision-makers in taking appropriate measures for a given situation and allows for identification of problem areas. The importance accorded to gender by those using GIS will determine whether it plays a significant role in relation to other factors during the decision-making process. It is therefore important to ensure that gender related variables are integrated into information that is transferred to GIS systems.
