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To give an overview of the gender-differentiated information sources to be taken into consideration at the beginning of and during an emergency operation.

Link: Needs Assessment Module.
Link: Partnerships Module.
Link: Human Resources Module.


Data collection, Decentralisation, Gender specific information, Information management systems, Information sources, Labour force surveys, Partnership, Population census, Primary and secondary data, Sex differentiated data.

Gender-Specific Information

Data disaggregated by sex and critical socio-economic categories are needed at all levels of policy formulation, planning, implementation, and monitoring. Integration of gender is emphatically not about creating a separate body of knowledge about women. It is about reconceptualising social and economic processes, to take better stock of gendered realities[13].

Macro-level aggregate statistics often do not show crucial differences within a population -addressing outcomes considerably more than the processes, and associated complex relationships among multiple variables, leading to such outcomes.

SEAGA Data Collection and Information Systems

Mixed Methods

  • Participatory research methodologies are increasingly widespread and well developed, and form the core of the SEAGA approach. A variety of tools facilitate two-way communication, and allow for understanding of complex processes and relationships at the micro-level. They can be more timely and cost-effective than formal survey methods.


  • Information systems that are designed to involve stakeholders at different levels and prioritize the needs of disadvantaged people should have structures for eliciting inputs at local levels. Decentralization involves institution-building at local (district and sub-district) levels of official information and planning agencies, with appropriate training, resources, and coordination provided to these levels and effective mechanisms at higher levels for receiving and incorporating this information into the policy-making process.


  • Along with decentralization, macro-level information systems should build in mechanisms for partnering with NGOs, universities, and private researchers to "channel synergies" and expand the vision and analysis underpinning policy.


  • "A shift from things to people, from blueprint to process, from hardware to software, and from the uniform to the diverse." Wider exposure to the practice of participatory techniques. Regular dialogue between front-line workers and planners.


  • Geographic Information Systems (GIS) offer new user-friendly technologies that facilitate storage of multiple types and levels of data in one database, and presentation of data in ways that demonstrate linkages between different levels and types of data.

They frequently contain conceptual, practical and logistical biases and anomalies. Concepts such as "work", "labour force", "production", "income", and heads of "household" are often not well structured. Women’s activities, often more varied, complex, and seasonal than men’s are, tend to fall outside established boundaries of what constitute "productive activities" or work.

People interviewed often fail to categorize their productive activities as "work". Their income may tend to be irregular and from varied sources, and they may often seek to conceal what they earn. If interviewers are male they may find themselves speaking only to male respondents, by choice or due to local cultural constraints or both. If interviewers visit households in the hours when the evening meal is being prepared, they may not be able to interview women.

Census data, while useful in analyzing long-term trends, are often of limited use in emergencies due to their infrequent collection, long gestation periods, and the limited number of variables they cover. They tend to be centralized, standardized, and simplified. Consequently, they may be ill equipped to deal with complex local realities and overlook remote or marginalized populations. They are often sectorally organized, so that useful data generated in one sector are not available to other sectors, and are not always readily usable, retrievable, or comprehensible.

Managers should realize that information about gender "does not come cheap". Not acquiring it may turn out a great deal more expensive in terms of projects that fail or are dysfunctional because the information on which they are based is faulty in that it lacks the gender-based perspective[14].

Many countries use specially commissioned sample surveys to gather data for specific purposes, at shorter intervals. These surveys, if appropriately designed, can be extremely useful in yielding information about the socio-economic and gender dimensions of development problems. The current state of the art in survey concepts and design, however, carries some built-in difficulties in addressing gender issues.

Different research and extension packages already popularized around the world, such as Farmer Participatory Research, Farming Systems Research Extension (FSRE), and Rapid Appraisal, incorporate participatory methodologies in different forms and to different degrees. Rapid Appraisals could be designed to provide some "typical" socio-economic profiles and gender relations models for different contexts within the country. These could help policy makers, for example, understand how different production incentive policies impact people at the field level.

Emergency Situation Information

Experience has shown that women (especially female-headed households) are often most vulnerable when an emergency occurs due to, amongst other factors, their frequently lower economic and social status.

In emergency operations, a quick response is essential and there is scant time available for lengthy surveys. Emergency operators are required to quickly analyse and integrate collected information and food security policy in view of designing appropriate responses, to restore and assist in ensuring the sustainability of the livelihoods of the affected and vulnerable population.

Sex-differentiated information is often insufficiently available in national and international databases. Women’s work in agriculture is largely unreported and underestimated in population censuses and labour force surveys. Existing databases are often not well developed and updated, and information is often scattered, anecdotal and conflicting. Further methodologies for surveying and analysing data may differ from country to country and among different institutions. Consequently data utilization by emergency operators can prove difficult, leading to constraints in effectively addressing gender issues.

Special efforts are being undertaken to improve measurement techniques in order to quantify more accurately the extent of female participation in agricultural work. For example the FAO Programme for the World Census of Agriculture 2000 has placed emphasis on various items that can provide gender-related structural information on agricultural activities[15].

Databases for sex-differentiated information for those responsible for impact assessment should be established. These should be integrated or linked to a Common International Database (CID) in the Food Insecurity Vulnerability Information Mapping System (FIVIMS). In order to protect all essential baseline data, which could eventually feed a database, these should be kept outside conflict-prone zones.

Critical Vulnerability of Some Population Segments

A post-Mitch analysis of selected social indicators has revealed critical vulnerabilities for women in the affected countries (Nicaragua, Honduras, Guatemala and El Salvador), that have provided some explanation on the differential gender effects of the Hurricane.

These countries had low life expectancy, and high maternal mortality, fertility, teenage pregnancy and illiteracy rates among rural women. Moreover, these societies were characterized by relatively high rates of female-headed households, mainly linked to civil and armed conflict in the region, with a consequent high male mortality and out-migration. The hurricane Mitch had a more severe impact in terms of men’s death and has thus exacerbated the situation increasing the number of female-headed households.

Population Censuses and Labour Force Surveys

Women should be accounted to be of economic importance by general systems of national accounting, as recommended by the International Labour Organization.

A population census might indicate women as not economically active, while other sources of information (sector surveys of planning institutions) may show women to be involved in productive activities such as fuel-wood collection. For example, in Pakistan, women’s economic participation varies from 3 percent (1981 Population Census) to 12 percent (Labour Force Survey). The Agriculture Census (1981) estimated that 73 percent of women in agriculture households were economically active. The Labour Force Survey (1990/91) showed women’s economic activity rates of 7 percent when using conventional questionnaires and 31 percent when considering questions on specific activities such as transplanting rice, picking cotton, grinding, drying seeds and tending livestock.

It is rarely possible to respond to high information demands in a rapidly changing emergency-situation. Conventional data-collection techniques may not be feasible and baseline information may not reflect the new reality. Rapid appraisal techniques (PRA) provide effective tools to consolidate information in a representative and efficient manner under emergency-situations.

A number of global and local information sources are available and can be utilized for emergency and contingency planning. UN agencies and NGOs also integrate national official data through country FIVIM, VAM and Early Warning systems and focal points.

In some complex disaster situations these sources might not be in existence, may be disrupted or not accessible for a variety of reasons. In such cases, the UN and other aid agencies may act as the sole custodians of up to date information.

WFP Vulnerability Assessment and Monitoring Network

The WFP World VAM Network currently provides food security analysis for 36 countries. It offers an information base for contingency planning and emergency needs assessment activities. It is also used to monitor changes in the food security of target groups, and assist in assessing progress made towards achieving Key WFP programme objectives.

To simplify data collection at country central level two statistical categories are typically identified that encompass most vulnerable groups, i.e., marginal farmers and the landless.

VAM systems use primary and secondary data sources (e.g. rapid assessments, key informant interviews and expert panel workshops) to fill important data gaps. For gender mainstreaming the WFP VAM system promotes the collection and analysis of sex-disaggregated data, the identification of gender based gaps or disparities and the design of graphic outputs which highlight gender disparities. Gender-sensitive approaches and techniques are integrated into rapid rural appraisals and emergency needs assessment analysis.

A common constraint in the integration of a gender perspective in the WFP VAM exercise is related to the lack of sex-disaggregation in secondary databases. Limited resources to collect and analyze primary data, to properly assess the specific needs of the target households (particularly women) are another constraint.

It is recommended that the user collects the most updated national agriculture censuses, general population censuses and periodical sample reports survey (on population, agriculture, food security) from relevant institutions at country level. As much gender-differentiated information should be extracted as possible, at sub-national disaggregation level.

The main objective of the WFP VAM network is to increase the effectiveness of WFP aid by improving the understanding of food security dynamics and the vulnerability to food insecurity. It provides an information base for contingency planning and emergency needs assessment and monitors changes in food security of the target groups, transferring skills and developing planning and analysis systems among local partners.

Example of Factors analyzed in VAM Missions

VAM’s activities are designed to:

  • Develop focused information products linked to WFPs programme

  • Define and target the most food insecure and vulnerable groups

  • Identify risks and constraints to improved food security

  • Carry out an inventory and map of local resource capabilities of partners

  • Identify indigenous capacities used to address food insecurity

  • Frame goals and objectives of country programmes

The FAO Global Information and Early Warning System (GIEWS)

The FAO Global Information and Early Warning System on Food and Agriculture (GIEWS), provides policy-makers and analysts up-to-date and accurate information on all aspects of food supply and demand. It produces periodic bulletins on food crop production and markets at global level and situation reports on a regional and country-by-country basis. GIEWS compiles and analyses information on global production, stocks, trades and food aid, export prices and main grain exchange developments. It reacts to emergency-situations by sending rapid evaluation missions to the countries affected and issuing Special Alerts reports that are quickly disseminated to the international community. The missions are often fielded jointly with WFP.

This system develops also new approaches and technologies for early warning and makes these available to national and regional early warning systems. GIEWS is closely linked for information sharing with governments, NGOs, other UN agencies, research institutions, the international press and private individuals.

Question Tank - Information

Information Sources Checklist

  • FAOSTAT and FAO relevant publications (e.g. Report on the 1990 World census of Agriculture)

Farming population. No. of agriculture holdings. Farm employment. Mechanisation level. Irrigation means. Data differentiated by sex/class/age. Extension worker/farmer ratio (gender audit of extension workers)

  • UNDP Annual Human Development Report

  • Population and Agriculture Censuses and Statistical Yearbooks

Socio-economic understanding, mortality, fertility, teenage pregnancy, life expectancy. Gender differentiated migratory patterns (temporary, seasonal and permanent trends)

  • UNESCO statistical yearbook

Literacy rates

  • UN statistical department

  • Regional Organisations (OAU, SADCC, ASEAN, I-ADB.)

Population differentiated by sex. Women members of parliament and ministers

  • Specialised Services (VAM, FIVMS, GIEWS, EMPRESS, FEWS, Economist Intelligence, and CIA)

Vulnerability, Nutritional status, Food intake, Dietary habits. National Food Supply and Demand, Animal/Plant Pests and Diseases, Dynamics of changes

Marginal Farmers Checklist

Main sources: Agriculture censuses and Agriculture Statistical Yearbooks

  • Landholding size

  • Livestock holdings by herd types and sizes

  • Holder’s sex, age, education, marital status and legal status with respect to owned/cultivated/held land.

  • Tenure status.

  • Crops (temporary, permanent).

  • Household size.

  • Composition of household by gender, age and type of relationship/dependency with holder.

  • Labour force participation by gender of landholding members.

  • Primary occupation by gender of landholding members.

  • Secondary occupation by gender of landholding members.

  • Hired workers by gender.

Landless Households Checklist

Main sources: Population and Agriculture Censuses, Integration with VAM, FIVIMS

  • Household size

  • Homestead sizes (gardening area)

  • Tenure status

  • Head’s sex, age, marital status and education

  • Household compositions by gender, age and type of relationship/dependency with head

  • Labour force participation by gender of members

  • Primary occupation by gender of members

  • Secondary occupation by gender of members

  • Available means of production

  • Crops preference

  • Livestock preference

Farmers in Production Checklist

Main sources: FAO Programme for the World Census of Agriculture 2000

  • Purpose of production

  • Land holders and members of their households by age, education and marital status

  • Main occupations and type of work [permanent, occasional]

  • Number and area of land and water holdings, land tenure and use, annual area of land cleared under shifting cultivation

  • Major temporary crops

  • Other temporary crops

  • Major permanent crops

  • Other permanent crops

  • Number and area of forest trees

  • Size of the holder’s households

  • Landholders and members of their households who are economically active by age

  • Holdings by number of permanent workers [member of the holder’s households and hired workers]

  • Use of high-yielding varieties

  • Use of fertilisers and pesticides

  • Number of each kind of livestock

  • Purpose of each kind of livestock

  • Fishery activities

  • Kinds of aqua-culture installations

  • Number of stationary power producing machinery by source of supply

  • Use of other agricultural machinery by source of supply

  • Building and other structures (use of non-residential buildings by tenure, area and volume of non-residential buildings by purpose)

[13] Source: Coelho, K. & Coffey, M., 1996. FAO Paper - Reversing the Flow: Toward Gender-Oriented Policy Information Systems in Agriculture.
[14] Source: Macdonald, M., 1994. Oxfam Paper - Gender Planning in Development Agencies: Meeting the Challenge. Oxford.
[15] Source: FAO, 1999. Filling the data gap - Gender-sensitive statistics for agricultural development. Rome. Pages 17-18.

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