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Population and housing census


  • + Uses of census data for gender statistics
    • For many countries, the population and housing census is an important source of data for gender statistics. There are several uses of census data for gender statistics. First, the population census is a primary source of benchmark gender statistics, covering not only the settled population but also the homeless population, nomadic groups and the population living in institutions. For example, population censuses provide benchmark information on living arrangements for older women and older men, the composition of immigrant stock by sex and other characteristics, lifetime fertility for older cohorts of women, educational attainment for women and men and gender segregation in occupations.

      Second, a unique feature of the census is its ability to generate statistics on small areas and small population groups with no or minimum sampling errors. This feature is important for gender statistics because a meaningful gender analysis often requires the disaggregation of statistics by various characteristics. For example, a gender gap in educational or economic characteristics may appear to be modest at the national level, but significant at the level of some population groups or some geographic areas. Large confidence intervals associated with sample surveys often make the comparison across groups difficult. Census data, in contrast, can easily be disaggregated by various background variables: age, religion, language, ethnicity, indigenous people, place of usual residence, marital status or wealth status of the household. For certain population groups or geographical areas, a population census may be the only source of information. For example, women and men belonging to minority groups, such as indigenous groups, migrants or older populations in remote areas, tend to represent a relatively small proportion of the population and tend to be harder to reach in household surveys. As a result, those groups of women and men are often not present in large enough numbers in survey samples to allow for calculations and analysis.

      Third, population censuses provide population counts for denominators needed to calculate various gender indicators based on data provided by administrative records, such as civil registration systems, school records or unemployment or employment registers. These population counts are usually disaggregated by sex, age and other characteristics collected in both the population censuses and administrative registers. For example, data on the population of school-age children by sex and single age group derived from population censuses, combined with information on school enrolment by sex, age, level and grade of education provided by school administrative records, are the basis for calculating gross or net enrolment rates for primary education or secondary education. Data on the female population aged 15 to 49 by age derived from population censuses, combined with data on number of births by age of mother provided by civil registration systems are the basis for calculating total and age-specific fertility rates.

      Lastly, in countries where civil registration systems have incomplete coverage, population censuses, along with household surveys, have a crucial role in providing gender statistics on fertility, mortality, marriages and migration. Compared to household surveys, population censuses have the advantage of eliminating sampling errors. This is an important feature, especially when measuring rare events such as maternal mortality, because it allows for the analysis of trends over time and in between various groups of population by eliminating the issue of large confidence intervals.

  • + Avoiding gender bias in data collection
    • Gender-based stereotypes can introduce serious biases in census data and the conclusions drawn from those data. There is much that can be done in the preparatory stages of the census to minimize gender-based biases, and this effort should be seen as part of the overall process of quality improvement of statistics. There are two broad types of preparatory activities: those related to census content and those related to census operations.

      Issues of census content, including what information is sought and how, the definitions and classifications used and the manner in which databases and tabulations are specified, are important to generate data needed to examine questions of gender equity. Producer-user consultations are a key element in defining the objectives and the scope of a census. Such users should be from governmental departments, ministries, universities and other research institutions, the private sector and other organizations (or individuals) representing the economic, social, educational and cultural life of a country. It is important that stakeholders concerned with gender equity be considered among the main groups of users and that they be included among advisory committees and subject-matter groups so that the gender concerns are taken into account from the planning stage of the census.

      With regard to census operations, particular attention will need to be given to census advertising; the selection, training and supervision of the field staff; and the evaluation of the results through re-interview surveys.

      Census advertising is an important tool for increasing the completeness of census coverage. The media campaign may be general, directed to all sections of the country and all segments of the population, or it may be aimed at specific segments of the population. Women may be considered a primary target of the advertising, especially in countries where a lot of underreporting is related to women. The choice of the type of media should take into account the fact that women may have easier access to some types of media than others. For example, in certain groups of population women are more likely than men to be illiterate.

      Women, girls and their contribution to the economy may become one of the subjects of the media campaign. For example, in India, a country which experienced in past censuses the massive underreporting of female members of the household and massive underreporting of women’s employment, a gender-specific strategy was designed: “The 2001 census logo, conceived as the flag-bearer for the Census of India, had a woman in front, leading the march into twenty-first century India; a woman enumerator enumerated the President of India, symbolically the first person to be counted in the census. This photograph, which made headlines in both electronic and print media, had the very positive effect of making women visible to the nation in the conduct of the census” (UNFPA, Country Technical Services Team for South and West Asia, 2004).

      Selection, training and supervision of the field staff involves ensuring that both men and women are recruited to the field staff (as both interviewers and supervisors) and that manuals and training materials cover gender bias issues just as they do other important sources of error (see boxes III.1 and III.2).

  • + Box III. 1 Designing the census questionnaire for better gender statistics: a checklist
    • Members of the team designing the questionnaire have been trained in gender-specific measurement issues related to each of the topics covered by the census

      There is a short note on the questionnaire on how to identify the head of household

      Categories of answers for marital status are detailed enough to capture various types of informal unions

      Questions on children ever born and children surviving allow separate answers for each sex

      Questions on fertility and child survival have a short note reminding the interviewer that he or she needs to seek information from the mother or, when the mother is missing, from another female member of the household

      Questions on pregnancy-related deaths have a short note reminding the interviewer that he or she needs to read them for all deaths of women aged 15 to 44

      The reference period for questions on economic activity, recent births, household deaths is clearly shown in the question

      Probing questions are included after the question on economic activity

      There is a short note on the use of activity lists for answering the questions on economic activity

      Questionnaire tests should cover both female and male respondents with different social backgrounds.

  • + Box III. 2 Checklist for preparation of census manuals and training of interviewers
    • Both women and men are selected as training instructors and appear as trainers presented in the audio-visual materials

      Gender-related measurement issues are reflected in the manual through descriptive examples and illustrated sketches

      The language and all the examples given in the manual or during training exercises are free of gender-based biases or other stereotypes related to the characteristics measured

      Training examples need to be reviewed so as not to foster gender-based or other stereotypes related to the characteristics measured

      Training provides guidelines regarding sex-selective underreporting or misreporting. Special attention should be dedicated to issues such as:

      - the criteria to identify the household head

      - the recording of the members of the household

      - selecting women as respondents when information on children ever born and children surviving is needed

      - the use of economic activity lists, including lists of own-account productive activities

      - the use of probing questions

Post-enumeration and re-interview surveys are important tools for evaluating coverage and content errors in census data collection. These errors refer to the underreporting or incorrect reporting or recording of the characteristics of persons, households and housing units enumerated in the census. From a gender perspective, it is important to make sure that there is no sex-selective underreporting or misreporting in the census. Characteristics referring to household memberships, births, deaths, or economic activity should be as fully reported for females as for males. In that regard, it is important to know whether the sex-selective underreporting or misreporting is the result of poorly phrased questions or instructions, proxy response, the sex of the interviewer or shortcomings related to the training and qualifications of interviewers, or to the result of coding or data entry mistakes. Post-enumeration and re-interview surveys should be used not only to calculate errors and/or correct census counts, but also to improve future data collections. The analysis of results from post-enumeration and re-interview surveys from previous censuses, from a gender perspective, should be used as input in redesigning census questionnaires and manuals and revising training exercises and materials.

  • + Topics covered
    • The paragraphs that follow show the topics recommended for collection in population and housing censuses (according to United Nations, 2008), their relevance for gender statistics and ways to improve data collection by integrating a gender perspective into data collection. It must be noted that most population censuses will cover only some of those topics. The selection of topics will depend on the needs of national users, alternative sources of data, the level of conceptual precision required to measure some of the topics and the demonstrated experience in collecting accurate data on such topics within the population census.
  • + Topics covered by population censuses

      Geographical and internal migration characteristics

      Relevance for gender statistics

      For some countries, population censuses may be the only source of gender statistics on internal migration. Information on the place of usual residence combined with information on place of birth, duration of residence, place of previous residence or, alternatively, place of residence at a specified date in the past, disaggregated by sex, can show the different patterns of internal migration for women and men. Among the patterns usually described are migration between rural and urban areas and migration between various regions of a country. Gender statistics in internal migration can be further disaggregated by other characteristics such as educational attainment or occupation. For example, data further disaggregated by educational attainment can show whether gender differences in migration patterns vary according to a person’s level of education. Data further disaggregated by occupation can show gender-differentiated patterns in labour migration.

      Information on the place of usual residence is used to define urban and rural areas and geographical and administrative areas, which are some of the most important breakdown variables for statistics in general and for gender statistics in particular. Urban and rural areas usually provide different ways of life, standards of living, education and employment opportunities and access to information, communication and technology. Women’s and men’s roles and expectations also vary between urban and rural areas. As a result, gender gaps in education or employment, for example, are different in the two types of residential areas. Similarly, different regions of a country may have different levels of development or different cultures, affecting the lives of women and men in different ways. Information on the place of usual residence can be used as an additional breakdown variable for sex and age disaggregated statistics on education, economic characteristics, household types or fertility, for example.

      Information on the place of usual residence disaggregated by sex, age and other variables can be used to identify groups of population in need of specific services that need to be provided locally. Examples of such groups are older women and men with disabilities who live in rural areas, or older women and men living alone in areas that are difficult to access.

      Certain population groups that may be covered only in a population census (although they may be excluded from counting in some cases) are of particular concern from a gender point of view, such as the homeless, nomads, persons living in areas that are difficult to access and refugees in camps. In such population groups, gender differences related to various characteristics may be different from the main population. It is therefore important that population data disaggregated by sex, age and other characteristics are provided for each of these groups.

      Population counts disaggregated by sex, age and place of usual residence can be used for the computation of vital statistics rates, such as age-specific fertility rates and age- and sex-specific mortality rates at the level of urban areas, rural areas or by region.

      International migration characteristics

      Relevance for gender statistics

      Population censuses are the best source for collecting data on immigrant stock. Questions regarding country of birth and country of citizenship provide information on the foreign-born population and the group of foreigners living in the country, respectively. Data on immigrant stock disaggregated by sex, age and other characteristics can reveal important gender differences. Migration patterns for women are often different than for men. Living arrangements and living conditions may also be different, for example, for young female migrants and young male migrants. Information on employment and occupation of foreign-born female and male populations can show whether female or male immigrant workers are more likely to be skilled and highly qualified. In addition, the gender gap in educational attainment or in employment and occupation in the migrant population may be different than that of the average population of the countries.

      Household and family characteristics

      Relevance for gender statistics

      Identification of household members, their relationship to the head or other reference member of the household and their grouping in family nuclei are the basis for deriving household and family composition and for distinguishing among different types of households. The information on living arrangements is an important input for understanding different situations of women and men with respect to the type of household or family they are part of and their position in it (for example, head or co-head). When sex, age and marital status of the household members are also taken into account, it is possible to identify certain types of households that tend to occur more frequently among women than men, such as one-person households of older persons or nuclear households of a parent with young children. Collecting information on household and family status further increases the possibility of identifying more types of living arrangements that tend to be different for women than for men. For example, lone mothers and lone fathers can be identified even when they are part of extended or composite households. Detailed living arrangements for female and male young adults or older persons can also be identified.

      Improving data collection from a gender perspective

      Countries should specify in their census design whether a household reference person or a household head is used to list all the household members. They should also clearly specify the criteria to be used to identify the reference person or the household head as a strategy for avoiding sex-based biases. Training materials and instructions should prevent the use of the assumption that women can be head of the household only when there are no adult males in the household. In countries where spouses are considered equal in household authority and responsibility and may share economic support of the household, (a) a reference member with no implication of headship may be chosen or (b) provision may be made for designation of joint headship.

      Sex-selective underreporting of household members to the disadvantage of women may occur in countries or groups of population where women have a lower status. The order of recording the members of the household has an impact on undercounting of women. In India, for example, the traditional approach in recording household members was to start with the head of the household, then to enumerate male members and afterwards the female members of the household (UNFPA, Country Technical Services Team for South and West Asia, 2004). As a result, the female members of the household and consequently the female population of the country were massively underreported. The new method involved in the census conducted in 2001 was to start with the head of the household and continue with others according to their age. Still, in many countries the omission of infants remains a common problem and sometimes girls may be more likely to be underreported than boys. The Principles and Recommendations for Population and Housing Censuses, Revision 2 (United Nations, 2008) recommends that members of the household be listed according to their family nucleus, if family nuclei are a topic of interest.

      Demographic and social characteristics

      Relevance for gender statistics

      Sex, together with age, represents the most basic type of demographic information collected for each individual in the population census. Of all the topics investigated in population censuses, sex and age are more frequently cross-classified with other characteristics of the population than any other topics. Sex disaggregation of data is a fundamental requirement for gender statistics. There are variations by sex for many socioeconomic and demographic characteristics collected through a census, such as education, economic activity, migration, disability or living arrangements. In addition, population counts by sex, age and other characteristics, combined with information from civil registration systems and other administrative records, are the basis for calculating age-specific fertility rates, sex- and age-specific mortality rates, enrolment rates for boys and girls and, sometimes, sex-disaggregated rates for employment or unemployment.

      Marital status, usually defined in relation to the marriage laws or customs of the countries, is basic demographic information necessary to identify particular forms of unions (such as consensual unions or polygamy), and certain marriage practices (such as child marriage) that are often to the disadvantage of women. Information on marital status can also show whether women tend to be found more often than men among the widowed, separated or divorced, which for women are statuses often associated with economic insecurity and lack of support in rearing children.

      Information on religion, ethnicity and indigenous peoples should be used as breakdown variables for gender statistics, especially when cultural factors are suspected to be one of the determinants of gender differences. For example, age at marriage for women, age gap between husband and wives, number of children born and educational attainment for women compared to men are often influenced by traditional practices, women’s status in society or preferences for sons. These factors tend to be more often observed among certain religious or ethnic groups. Nevertheless, questions regarding religion, ethnicity and indigenous peoples are sensitive questions and their inclusion in the census should be carefully considered.

      Improving data collection from a gender perspective

      Use of detailed categories of marital status that would capture various forms of informal unions improves the adequacy gender statistics. The Principles and Recommendations for Population and Housing Censuses, Revision 2 recommends that at least five categories of marital status be identified for each individual in relation to the marriage laws or customs of the country: (a) single or never married; (b) married; (c) widowed and not remarried; (d) divorced and not remarried; (e) married but separated – legally or de facto separated. From a gender perspective, however, it is important to have more detailed categories, reflecting various types of unions. In some countries, additional categories are included in the marital status classification, including customary unions, such as registered partnerships and consensual unions, which are legal and binding under law, or persons who are contractually married but not yet living together as husband and wife. Some countries may distinguish between formal marriages and de facto unions, and between persons legally separated and those legally divorced. Although not common, the collection of additional information related to polygamous or polyandrous marital status is needed in some countries.

      Fertility and mortality

      Relevance for gender statistics

      Population censuses are an important source of data on fertility in countries that lack a timely and reliable system of vital statistics. In this context, information on recent fertility of women can be derived from the information on the date of birth of last child born. Information on the number of children ever born by women should be collected in the census even in countries with reliable vital registration of births. This topic can be useful not only for estimating levels of lifetime fertility for older cohorts of women, but also for assessing the completeness of the registration system.

      In countries with civil registration systems with incomplete coverage, information on children ever born and children surviving, disaggregated by sex of the children and age of mothers, can be used to calculate child mortality rates for girls and boys. Usually there is a gender gap in child mortality to the disadvantage of boys, mainly due to biological factors.

      For adults as well as children, information on household deaths in the past 12 months by sex of deceased and age at death may be used to estimate the level and pattern of female and male mortality. In addition, by asking follow-up questions concerning cause of death, some countries are able to collect data on pregnancy-related deaths that can be used to estimate maternal mortality. Data on adult female and male deaths may also be obtained by using indirect approaches such as the maternal or paternal orphanhood method, however, the adequacy of adult mortality data obtained through this indirect method from the population censuses is still uncertain.

      When age at first marriage and age of mother at the time of first birth are included in the census questionnaire, additional information on child marriage and adolescent births can be obtained. This information is important because women are more likely than men to have an early marriage and to become parents while still adolescent, with consequences in terms of health, schooling and lifetime prospects for employment and career.

      Improving data collection from a gender perspective

      A more complete and accurate reporting of children ever born and children surviving is obtained when the information is collected separately for each sex.

      As far as possible, efforts should be made to obtain information on fertility, child mortality (or survival) and marriage directly from the woman or mother involved, because she is more likely to recall correctly the details of her fertility, the mortality of her offspring and her marital experiences than any other member of the household.

      Some of the misclassification of adult female deaths as non-maternal may be prevented by proper training of the interviewers. When collecting data on maternal mortality, the questions used to identify pregnancy-related deaths – such as “Was the woman pregnant, giving birth or within six weeks after the end of pregnancy or childbirth at the time of her death?” – should be asked even in cases in which respondents voluntarily offer information on cause of death.

      Educational characteristics

      Relevance for gender statistics

      Population censuses provide benchmark gender statistics on education, covering population groups often not included in the sample of household surveys, such as the homeless population, the nomad population, or persons living in institutions. Data on literacy, school attendance and educational attainment disaggregated by sex, age and place of usual residence are crucial for understanding gender disparities in access to education across a country and changes in education gender gaps by cohort.

      Population counts by sex, age and literacy or by sex, age and educational attainment can be used as denominators for calculating important gender indicators such as birth rates by mother’s education, child mortality rates by mother’s education, female and male age-specific death rates by educational attainment and employment or unemployment rates for women and men by educational attainment.

      Improving data collection from a gender perspective

      Data on school attendance, educational attainment and literacy status should be collected and tabulated separately and independently of each other, without any assumption of linkages between them. In operational terms, this means inquiring systematically about the literacy status of each household member irrespective of school attendance or highest grade or level completed.

      The United Nations Educational, Scientific and Cultural Organization (UNESCO) recommends that literacy tests should be administered in order to verify, as well as improve, the quality of literacy data. Nevertheless, administering a literacy test to all household members may prove impractical in the census and affect the overall participation, therefore limiting the utility of the results. Countries have regularly used simple self-reporting to provide an indication of literacy rates at the small area level (United Nations, 2008). When the reporting is done by a third person (the reference person or the head of household, for example) the literacy level for women and children may be overestimated (UNESCO Institute for Statistics, 2008).

      Economic characteristics

      Relevance for gender statistics

      Statistics on economic characteristics disaggregated by sex and age can show the contribution of women and men to the economy, gender differences in employment conditions and gender segregation in the labour market. For a meaningful gender analysis, these data should be further disaggregated by other characteristics. For example, gender segregation in the labour market is partially determined by the gender gap in education, therefore data on occupations should be further disaggregated by level of educational attainment. Gender differences in employment conditions depend on the structure of local job markets, therefore data on activity status and status in employment should be further disaggregated by place of residence (urban/rural areas or by region).

      Several types of economic characteristics that are important from a gender perspective may be difficult to collect in the population censuses, particularly in countries with less developed statistical systems (United Nations, ILO, 2010). For example, although income is an important topic for understanding economic gender gaps, it is difficult to collect reliable information on the value of home production and the value of income paid in kind. These are extremely important components of the total income for individuals and households in most developing countries, but measurement is extremely difficult and complex even in household surveys. Even when confined to cash income, the collection of income data in a population census may present special problems in terms of the respondent’s burden and response errors. Nevertheless, some developed countries have a long history of collecting detailed cash income information at the individual level.

      There is limited experience in collecting in the census data on time-related underemployment, informal sector and informal employment (United Nations, ILO, 2010). These topics are usually relevant from a gender point of view, but more testing is needed before deciding whether it is possible and worthwhile to include them in the census. Similarly, although the “usual activity” approach in measuring economically active population may better reflect the seasonal fluctuations of activities often associated with women’s work, it may be more difficult to implement in a population census. The “usual activity” approach implies a bigger burden and is subject to more recall errors, compared to the “current activity” approach.

      Improving data collection from a gender perspective

      The risk of misclassifying women as homemakers is reduced when basic questions on economic activity and status in employment are supplemented by further probing questions, or when more detailed questions are included in a self-administered questionnaire.

      The proper identification of activities that are economic is also helped by the use of activity lists. It is advisable for countries to develop an extensive list of own-account production activities considered to be within the System of National Accounts production boundary, so as to ensure that those involved in such activities are correctly classified as economically active. In principle, the production of all goods falls within the System of National Accounts production boundary, irrespective of whether the goods are intended for supply to other units or for the producers’ own final use. In practice, however, the production of a good for own final use within households is recorded only if the amount of the good produced by households for their own final use is believed to be quantitatively important in relation to the total supply of that good in a country. According to the Thirteenth International Conference of Labour Statisticians, persons engaged in the production of goods for own final use within the same household should be considered economically active only if such production comprises an important contribution to the total consumption of the household.

      Lists of own-account production activities could include, for example, the production of agricultural products and their subsequent storage; the production of other primary products such as the mining of salt, the cutting of peat, the supply of water; the processing of agricultural products (the preparation of meals for own consumption is excluded); and other kinds of processing, such as weaving cloth, dressmaking and tailoring; the production of footwear, pottery, utensils or durables; the making of furniture or furnishings; and major renovations, extensions to dwellings, the replastering of walls or the re-roofing by owners of owner-occupied dwellings. For example, in the preparation for the 2001 census in India, 32 sketches showing different types of women’s work that is not usually reported were included in the interviewer manual (UNFPA, Country Technical Services Team for South and West Asia, 2004).

      The questions on occupation should seek full details in order to capture relevant differences between women and men. The questions should be phrased to capture (a) the title of the job and (b) a statement about the main tasks and duties performed. The word “occupation” can be misleading, in some circumstances, and may best be either left out of actual questions on the topic or supplemented with a more easily understood word. The concern is that some of the economic activities of women may be left out and the occupations of women may be underreported because they are not qualified in the view of respondent or the interviewer as occupations. For developing countries where translation in the field is very common, the terminology being used by interviewers in the local language should be carefully checked during testing and training periods.

  • + Topics covered by housing censuses
    • The topics covered by the housing censuses are important for understanding living conditions as they affect women and men’s lives. Among all topics covered by the housing censuses, several in particular are important for gender statistics.

      Relevance for gender statistics

      Types of living quarters. In many countries, population and housing census are the only source of gender statistics for populations living in certain types of living quarters, such as retirement homes and homes for elderly, orphanages, refugee camps and camps for internally displaced people. It is important that population data disaggregated by sex, age and other characteristics be provided for each of these types of living quarters. The data can show, for example, whether more women than men are in retirement homes and homes for elderly, and their marital status. Data on population in orphanages disaggregated by sex, age and school attendance can show whether girls or boys are more likely to be found in this type of institution and whether there is a gender gap in educational participation.

      Ownership of housing property. Population and housing censuses can be used to improve the knowledge of women’s and men’s ownership of housing property. In some countries with available data, it has been shown that women are less likely than men to be owners of property. Most of the time, however, data are collected at household level, without taking into account a joint ownership. Still, some countries have inquired in their censuses about property ownership by sex. For example, in the 2001 census in Nepal, for the self-owned housing properties, a question was added regarding whether they were owned by female or male members of the household (UNFPA, Country Technical Services Team for South and West Asia, 2004).

      Main source of drinking water. Some of the questions covered in the housing census provide important background information for understanding some of the work burden of women and men. Census data on the water supply system and main source of drinking water will provide information on the number of households with lack of access to water within the building or within 200 metres. In many countries, these are households where mainly women have an additional burden of work, as women are in charge of water collection more often than men (United Nations, 2010).

      Fuels used for cooking. Housing census questions on fuels used for cooking provide important background information on issues of gender and environmental health. Members of households using solid fuels are exposed to indoor smoke, and women are more likely to develop acute respiratory infections, obstructive pulmonary disease and lung cancer, because they spend more time cooking and near fire (United Nations, 2010).

  • + References
    • Hedman, Birgitta, Francesca Perucci and Pehr Sundström (1996). Engendering Statistics: A Tool for Change. Stockholm: Statistics Sweden.

      United Nations (2008). Principles and Recommendations for Population and Housing Censuses, Revision 2. Statistical papers, Series M, No.67/Rev.2. Sales No. E.07.XVII.8.

      ___ (2010). The World’s Women 2010: Trends and Statistics. Series K, No. 19. Sales No. E.10.XVII.11.

      ___and International Labour Office (2010). Measuring the Economically Active in Population Censuses: A Handbook. Studies in Methods, Series F, No.102. Sales No. E.09.XVII.7.

      United Nations Educational, Scientific and Cultural Organization, Institute for Statistics (2008). International Literacy Statistics: A Review of Concepts, Methodology and Current Data. Montreal.

      United Nations Population Fund, Country Technical Services Team for South and West Asia (2004). Report of the Regional Knowledge Sharing Workshop on Engendering Population Census in South and West Asia. Kathmandu, Nepal, 8-10 March.

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