{"doc_desc":{"title":"National Panel Survey  2010-2011","idno":"DDI-TZA-NBS-NPS-Wave2","producers":[{"name":"National Bureau of Statistics","abbreviation":"NBS","affiliation":"","role":"Survey Implementer"},{"name":"Accelerated Data Program","abbreviation":"ADP","affiliation":"PARIS21","role":"Review of the metadata"}],"prod_date":"2012-09-25","version_statement":{"version":"Wave 2:  Anonymous dataset for public distribution."}},"study_desc":{"title_statement":{"idno":"TZA-NBS-NPS-2010-V01","title":"National Panel Survey Report 2010-2011","sub_title":"Wave 2","alt_title":"NPS 2010"},"authoring_entity":[{"name":"National Bureau of Statistics  Nationa Bureau of Statistics","affiliation":"Survey Implementer"}],"oth_id":[{"name":"Poverty Eradication Division","affiliation":"","email":"","role":"Main supporters"},{"name":"Gates Foundation,","affiliation":"","email":"","role":"Main supporters"}],"production_statement":{"producers":[{"name":"Ministry of Agriculture, Food Security and Cooperatives","affiliation":"Line Ministries","role":"- [Technical assistance in] survey design and implementation"},{"name":"Ministry of Finance","affiliation":"Line Ministries","role":"- [Technical assistance in] survey design and implementation"},{"name":"Millennium Challenge Account - Tanzania","affiliation":"Mof","role":"- [Technical assistance in] survey design and implementation"},{"name":"World Bank","affiliation":"Development partners","role":"- [Technical assistance in] survey design and implementation"},{"name":"Department for International Development","affiliation":"Development partners","role":"- [Technical assistance in] survey design and implementation"},{"name":"United Nation Children's Funds","affiliation":"development partners","role":"- [Technical assistance in] survey design and implementation"},{"name":"United Nation  Population Funds","affiliation":"development partners","role":"- [Technical assistance in] survey design and implementation"},{"name":"Japan International Cooperation Agency","affiliation":"development partners","role":"- [Technical assistance in] survey design and implementation"}],"copyright":"(c) 2012, National Bureau of Statistics","funding_agencies":[{"name":"The European Commission","abbreviation":"EU_Commission","role":"Provide grant "},{"name":"The World Bank(Living Standards Measurement Study - Integrated Surveys on Agriculture)","abbreviation":"WB_LSMS-ISA","role":"Provide complementary funding"}]},"distribution_statement":{"contact":[{"name":"Director General","affiliation":"","email":"dg@nbs.go.tz","uri":"http://nbs.go.tz/index.php?option=com_contact&view=contact&id=1&Itemid=69"}]},"series_statement":{"series_name":"Multiple Indicator Cluster Survey - Round 2 [hh/mics-2]","series_info":"The 2010/2011 Tanzania National Panel Survey (TZNPS) is the second in a series of nationally representative household panel surveys that collect information on a wide range of topics including agricultural production, non-farm income generating activities, consumption expenditures, and a wealth of other socio-economic characteristics. Both the first and second rounds of the TZNPS were implemented by the Tanzania National Bureau of Statistics (NBS). The first round of the survey was conducted over twelve months from October 2008 to September 2009."},"version_statement":{"version":"v0.1:  Edited, anonymous dataset for public distribution.","version_date":"2012-09"},"study_info":{"keywords":[{"keyword":"NPS","vocab":"","uri":""},{"keyword":"National Panel Survey","vocab":"","uri":""}],"topics":[{"topic":"Agricultural production","vocab":"","uri":""},{"topic":"Non-farm income generating activities","vocab":"","uri":""},{"topic":"Consumption expenditures","vocab":"","uri":""},{"topic":"Wealth of other socio-economic characteristics","vocab":"","uri":""}],"abstract":"The main objective of the TZNPS is to provide high-quality household-level data to the Tanzanian government and other stakeholders for monitoring poverty dynamics, tracking the progress of the Mkukuta poverty reduction strategy1, and to evaluate the impact of other major, national-level government policy initiatives. As an integrated survey covering a number of different socioeconomic factors, it compliments other more narrowly focused survey efforts, such as the Demographic and Health Survey on health, the Integrated Labour Force Survey on labour markets, the Household Budget Survey on expenditure, and the National Sample Census of Agriculture. Secondly, as a panel household survey in which the same households are revisited over time, the TZNPS allows for the study of poverty and welfare transitions and the determinants of living standard changes.","coll_dates":[{"start":"2010-10","end":"2011-09","cycle":""}],"nation":[{"name":"Tanzania","abbreviation":""}],"geog_coverage":"Dar es Salaam, other urban areas in Mainland, rural areas in Mainland, and Zanzibar","geog_unit":"National","analysis_unit":"Household , Agriculture, Fishery and Community","data_kind":"Sample survey data [ssd]","notes":"- HOUSEHOLD: Household Identification, Household Member Roster, Eduaction, Health, Labour, Food Outside the Household, Subject welfare, Government, Food Security, Housing, Water and Sanitation, Food Consumption,Non-Food Expenditures,Household Assets, Assistance and Groups, Credit, Finance, Recent Shocks to HH Welfare, Anthropometry\n\n- AGRICULTURE:Household Roster, Plot Roster, Plot Details, Annual Crops by plot, Annual Crop Production and Sales, Permanent Crops by plot, Permanent crops - production and sales, Outgrower schemes and contract farming, processed agricultural products and agricultural bi-products, livestock, Farm implents and machinery extension \n\n- FISHERY:Survey Information, fisheries Calendar, household labour, Fishing Labour, input, output, Gear Rentet out, trading.\n\n- COMMUNITY: Community Identification, Survey staff Details, Access to basic services, Investments projects, land use,, Agriculture, Demography and family issues, Governance, Water and sanitation, Roster of Community leaders, Market price."},"method":{"data_collection":{"data_collectors":[{"name":"National Bureau of Statistics","abbreviation":"NBS","affiliation":""}],"sampling_procedure":"The sample design for the second round of the NPS revisits all the households interviewed in the first round of the panel, as well as tracking adult split-off household members. The original sample size of 3,265 households was designed to representative at the national, urban/rural, and major agro-ecological zones. The total sample size was 3,265 households in 409 Enumeration Areas (2,063 households in rural areas and 1,202 urban areas). It is also be possible in the final\nanalysis to produce disaggregated poverty rates for 4 different strata: Dar es Salaam, other urban areas on mainland Tanzania, rural mainland Tanzania, and Zanzibar\n\nSince the TZNPS is a panel survey, the second round of the fieldwork revisits all households originally interviewed during round one. If a household has moved from its original location, the members were interviewed in their new location. If that location was within one hour of the original location, the field team did the interview at the time of their visit to the enumeration area. If the household had located more than an hour from the original location, details of the new location were recorded on specialized forms, and the information passed to a dedicated tracking team for follow-up.\n\nIf a member of the original household had split from their original location to form or join a new household, information was recorded on the current whereabouts of this member. All adult former household members (those over the age of 15) were tracked to their new location. Similar to the protocol for the re-located households, if the new household is within one hour of the original location, the new household was interviewed by the main field team at the time of the visit to the enumeration area. For those that have moved more than one hour away, their information was passed to the dedicated tracking team for follow-up. Once the tracking targets have been found, teams are required to interview them and any new members of the household.\n\nThe total sample size for the second round of the NPS has a total sample size of 3924 households. This represents 3168 round-one households, a re-interview rate of over 97 percent. In addition, of the 10,420 eligible adults (over age 15 in 2010), 9,338 were re-interviewed, a reinterview rate of approximately 90 percent.","sampling_deviation":"To obtain the attrition adjustment factor the probability that a sample household was successfully reinterviewed\nin the second round of surveys is modeled with the linear logistic model at the level of the individual. A binary response variable is created by coding the response disposition for eligible households that do not respond in the second round as 0, and households that do respond as 1. Then a logistic response propensity model is fitted, using 2005 UNHS household and individual characteristics measured in the first wave as covariates.\n\nIn a few limited cases, values of unit level variables were missing from the 2008/2009 household dataset. These values were imputed using multivariate regression and logistic regression techniques. Imputations are done using the \u2018impute\u2019 command in Stata at the level of the UNPS strata (urban/rural and region). Overall, less than one percent of the variables required imputation to replace missing values.\n\nThe estimated logistic model is used to obtain a predicted probability of response for each household member in the 2010/2011 survey. These response probabilities were then aggregated to the household level (by calculating the mean), the using the household-level predicted response probabilities as the ranking variable, all households are ranked into 10 equal groups (deciles). An attrition adjustment factor was then defined as the reciprocal of the empirical response rate for the household-level propensity score decile.\n\nTo reduce the overall standard errors, and weight the population totals up to the known population figures, a post-stratification correction is applied. Based on the projected number of households in the urban and rural segments of each region, adjustment factors are calculated. This correction also reduces overall standard errors (see Little et al, 1997).","coll_mode":["Face-to-face [f2f]"],"research_instrument":"The Household Questionnaire is comprised of thematic sections.This comprehensive questionnaire allows\nfor the construction of a full consumption-based welfare measure, permitting distributional and incidence analysis. This project also recognizes the imperative to look beyond the household as a unit of analysis in order to improve the quality, relevance and sustainability of agricultural data systems. Although data collection is structured around a household panel survey, the data on labor, education, and health status were collected at the individual level. Moreover, in some household activities (like non-farm enterprise), the questionnaire records which specific\nmembers are engaged in the activity. A detailed description of the contents of the questionnaire can be found in the Basic Information Document report (Table 1). \n\nThe Agricultural Questionnaire collects information relative to a household\u2019s agricultural activities. Information is collected at both the plot and crop level on inputs, production and sales. The Basic Information Document report (Table 2) provides a detailed description of the contents of the questionnaire. This questionnaire was administered to any household that engaged in any farming or livestock holding.\n\nThe Fisheries Questionnaire was developed in partnership with the World Fish Program to collect data on household fishery activities, fish processing, and fish trading. This includes data on the inputs, outputs, labour, and sales. All this data is divided into two reference periods, the high and low season. This data is collected at the household level. The Basic Information Document report (Table 3) provides a more comprehensive list of the sections found within the Fishery Questionnaire.\n\nThe Community Questionnaire collects information on physical and economic infrastructure and\nevents in surveyed communities3, as described in The Basic Information Document report (Table 4). In each selected survey community, key informants are interviewed by the field team supervisors. Information about the respondents for the community questionnaire is collected individually in section CI of community questionnaire.\n\nThe questionnaires were developed in collaboration with line ministries and donor partners, including the Technical Committee, over a period of several months. The NBS solicited feedback from various stakeholders in regards to survey content and design. The round two questionnaires were piloted in the Morogoro region in June 2010, in conjunction with supervisor training. After piloting, the questionnaires were further revised and finalized by August 2010. Questionnaire manuals were developed with detailed instructions for field staff during training and as the main survey reference guide over the course of the field work.","coll_situation":"The survey was implemented by eight mobile field teams, each composed of: one supervisor, four enumerators, one data entry technician, and one driver.\n\nThe teams visited each enumeration area for between 4-5 days. The questionnaires were administered to the selected households over the course of that time. This allowed the field team to make return visits to the household to complete the entire Household questionnaire and, for farm households, Agriculture questionnaires, and for Fishery questionnaires. To ensure the depth and quality of each section of the survey, the questionnaire was administered across multiple respondents to the most knowledgeable about each topic. For all of the sampled households, areas of all owned and/or cultivated agricultural plots were measured via GPS unless the household refused, the terrain was too difficult, or if the plot was more than 1 hour from the\nlocation of the household. Anthropometric measurements were taken for all individuals that were\nat home, not too ill, and willing to participate\n\nIf the field teams enter an enumeration area and find that the entire household or a member(s) of the household has moved, they are required to follow the tracking protocol. If the entire household has moved from the original residence, teams are required to fill a T-1 form. The T-1 form contains information on the new location of the household, allowing for the teams to locate and interview the household members. If a member or members of the household have split from the original household, a T-2 form is filled out by the teams. Similar to the T-1, a T-2 form contains information on the location of the member(s) who have split from the household. Once the tracking targets have been found, teams are required to interview them and any new additions to the household. Out of the tracking individuals/households, only those over 15 years of age are included in the tracking protocol unless an individual under 15 years of age moved with another individual over 15 years of age, and both were part of the round one data collection\n\nWithin the tracking protocol, there are local and distance cases. Local and distance tracking applies to both T-1 and T-2 forms. Local tracking occurred when the tracking target is within one hour traveling distance from the original EA and at least one tracking member from the household is over 15 years of age. If that is the case, the teams are required to interview the tracking target before leaving the original EA. Distance tracking occurs when the tracking target is not within one hour traveling distance from the original EA. In this case, the teams fill out the appropriate tracking form and send the information NBS headquarters. Once at NBS, the distance tracking case is given to the tracking team, who is then responsible for locating that household and conducting the interview.\n\nThe mobile tracking team consisted of one supervisor, two interviewers, one data entry technician, and one driver. In addition, there were two dedicated tracking enumerators that remained in Dar es Salaam. The tracking team began interviews three months after the beginning of fieldwork to allow enough time to accumulate a sufficient number of tracking targets. Tracking targets were grouped into geographic regions, and the team would visit the regions approximately every 2-3 months. Any tracking target not located was remained in the pool to be visited during the next trip, in addition to any new tracking cases that had accumulated in the intervening months. In addition, the regular field teams also sporadically would perform\ntracking within their interview regions if there was a backlog of cases. Finally, following the completion of the main fieldwork activities, four supervisors led dedicated tracking teams to interview the remaining cases.\n\nData entry was done concurrently with data collection by the data entry technician, using a laptop, known as first data entry. The data entry program was a CSPro-based system, developed by NBS with support from the World Bank. This facilitated the performance of internal crosschecks prior to departure from the enumeration area, allowing enumerators to return to households and clarify inconsistent information on the questionnaires. Data files from completed EAs were then e-mailed to headquarters using 3G modems. These files were\nconcatenated and periodic checks were done to ensure the fieldwork was proceeding according to the calendar. The field teams also send the paper questionnaires back to the headquarters on a monthly basis.\n\nOnce the paper questionnaires and data files for completed EAs were received at NBS headquarters, a double entry procedure was implemented. Eight data entrants were hired by NBS to re-enter the data from the paper questionnaires into the CSPro-based data entry system for all households and questionnaires administered. A cross comparison between the entered values in the field based data entry and double entry was conducted and any differences in values between the two were flagged for manual inspection of the physical questionnaire. Corrections based on this inspection exercise were ultimately encoded in the dataset.\n\nAdditionally, an extensive review of data files was conducted, including interviewer errors such as missing values, ranges and outliers. Observations were returned for manual inspection of the physical questionnaires if continuous values fell outside five standard deviations of the mean, categorical values were not eligible responses, or there were internal inconsistencies within the dataset (for example, the age of an individual was not consistent with their educational status, there was more than one head of household listed, an individual was engaged in multiple primary activities, the quantity of crops and their byproducts produced, harvested, and sold not listed, the distance from the market and an individual\u2019s plot was not listed, the number of weeks, days per week, and hours per day an individual engaged in fishery activity was not recorded, the species and quantity of fish caught, bought, sold, or traded was not listed, etc).\n\nWhen it was determined that these values were the result of data-entry error, the values were corrected. In addition, cases deemed to reflect obvious enumerator error were also corrected in this cleaning process. The majority of such cases involved the use of incorrect measurement units, e.g. recording grams as kilograms or vice versa.","act_min":"The mobile tracking team consisted of one supervisor, two interviewers, one data entry\ntechnician, and one driver. In addition, there were two dedicated tracking enumerators that\nremained in Dar es Salaam. The tracking team began interviews three months after the\nbeginning of fieldwork to allow enough time to accumulate a sufficient number of tracking\ntargets. Tracking targets were grouped into geographic regions, and the team would visit the\nregions approximately every 2-3 months. Any tracking target not located was remained in the\npool to be visited during the next trip, in addition to any new tracking cases that had accumulated\nin the intervening months. In addition, the regular field teams also sporadically would perform\ntracking within their interview regions if there was a backlog of cases. Finally, following the\ncompletion of the main fieldwork activities, four supervisors led dedicated tracking teams to\ninterview the remaining cases.","weight":"The methodology described in this paper builds upon published documentation from established panel surveys, such as the Panel Study of Income Dynamics [PSID], conducted since 1968 by the Institute for Social Research at the University of Michigan; and the British Household Panel Survey [BHPS], whose first 13 waves were conducted between 1991 and 2003 by Institute for Social and Economic Research at the University of Essex. Both the PSID and the BHPS are nationally-representative panel surveys in the USA and the UK respectively.\n\nThe weights are developed following these steps:\n1) Begin with the \u201cbase weights\u201d or those calculated during the first round of the survey;\nThe panel weight calculations are based on the 2008/2009 household weights. These weights are based\non the inverse probability of selection, EA level non-response correction, trimming of outlier weights, and\na post-stratification correction11. These probability weights form the first component of the 2010/2011\ncalculations.\n              W1=W2008\n\n2) incorporate fair-share weights for composition changes;\nBased on the tracking protocols, the tracking for split off rules for the TZNPS allow for the incorporation of people who now live with original sample members. For example a young adult living with his parents in 2008, may be 2010 have formed a new household, getting married and having a child. The wife and infant will be incorporated into the survey and thus require a probability of selection. Such corrections are routinely used to distribute weight to new sample members in panel surveys. See Rendtel and Harms (2009) for a discussion of several different methods of weight correction. Because split-off individuals are tracked and interviewed in their new households, there are multiple ways\nthat a household can become part of the survey. \n\no Either by being selected initially for the first round of the TZNPS\no By receiving a member that came from a household that was selected for the first round of the\nTZNPS.\n\nIn an ideal world, it would be possible to know the probability of selection that each new member brought\ninto the household, and adjust the household weight accordingly. This is necessary since households\nreceiving members have higher probabilities of selection (and therefore lower weights) because the\nhousehold could have been selected in multiple ways. Since we cannot know the probabilities of every\nmember, we must make simplifying assumptions. The first simplifying assumption is that the arriving\nmembers arrived together from one other household. This would be the case if a man and woman get\nmarried and set up a new household, or in the case of an older relative moving in with adult children. In\ncertain cases, however, arriving members come from more than one household. Assuming only two\nsource households underestimates slightly the probability of selection (and therefore over-estimates the\nweights). Incidence of these cases is believed to be relatively rare, and any resulting bias should be\nnegligible. The second simplifying assumption we make is that the arriving members have the same\nprobability of selection, on average, as those members that are already there. This would not be true on a\ncase-by-case basis but would be true in the aggregate. With these simplifying assumptions, we add a\nfactor of \u00bd for all households, \u2018split\u2019 or \u2018parent\u2019 that have new members arriving from other households.\nThis takes into account the fact that they could have been selected in two ways, and assumes the\nprobability of selection is equal\n\nA limitation of the panel methodology is that the represented population is not identical to the 2010\nTanzanian household population, as it does not include immigrants in new households. Inclusion of these\ngroups would necessitate refreshing the sample with new households. However, the represented\npopulation is close enough to the 2010 Tanzanian population to permit the desired cross-sectional\nestimates.\n\n3) derive attrition adjusted weights for all individuals, including split-off10 households, then\naggregate these weights to the household level;\nAll household panel surveys must tackle the problem of attrition, sample members selected for follow\ninterview which cannot be located and/or interviewed. The methodology used to adjust weights for\nattrition in the UNPS follows Rosenbaum & Rubin (1984). We use predicted response probabilities from\na logistic regression model based on the covariates to form the weighting classes or cells. This approach\nhas also been adopted in the PSID; see for example, Gouskova (2008).\n\nThe total sample size for the second round of the NPS has a total sample size of 3924 households. This\nrepresents 3168 round one households, a re-interview rate of over 97 percent. In addition, of the 10,420\neligible adults (over age 15 in 2010), 9,338 were re-interviewed, a re-interview rate of approximately 90\npercent.\nTo obtain the attrition adjustment factor the probability that a sample household was successfully reinterviewed\nin the second round of surveys is modeled with the linear logistic model at the level of the\nindividual. A binary response variable is created by coding the response disposition for eligible\nhouseholds that do not respond in the second round as 0, and households that do respond as 1.\n\nThen a logistic response propensity model is fitted, using 2005 UNHS household and individual\ncharacteristics measured in the first wave as covariates.\nIn a few limited cases, values of unit level variables were missing from the 2008/2009 household dataset.\nThese values were imputed using multivariate regression and logistic regression techniques. Imputations\nare done using the \u2018impute\u2019 command in Stata at the level of the UNPS strata (urban/rural and region).\nOverall, less than one percent of the variables required imputation to replace missing values.\nThe estimated logistic model is used to obtain a predicted probability of response for each household\nmember in the 2010/2011 survey. These response probabilities were then aggregated to the household\nlevel (by calculating the mean), the using the household-level predicted response probabilities as the\nranking variable, all households are ranked into 10 equal groups (deciles). An attrition adjustment factor\nwas then defined as the reciprocal of the empirical response rate for the household-level propensity score\ndecile.\n\n4) post-stratify the pooled weights to known population totals.\n\nTo reduce the overall standard errors, and weight the population totals up to the known population\nfigures, a post-stratification correction is applied. Based on the projected number of households in the\nurban and rural segments of each region, adjustment factors are calculated. This correction also reduces\noverall standard errors (see Little et al, 1997).","cleaning_operations":"CSPro-based data entry/editing system was used.\n\n A cross comparison between the entered values in the field based data entry and double entry was conducted and any differences in values between the two were flagged for manual inspection of the physical questionnaire. Corrections based on this inspection exercise were ultimately encoded in the dataset.\n\nAdditionally, an extensive review of data files was conducted, including interviewer errors such as missing values, ranges and outliers. Observations were returned for manual inspection of the physical questionnaires if continuous values fell outside five standard deviations of the mean, categorical values were not eligible responses, or there were internal inconsistencies within the dataset (for example, the age of an individual was not consistent with their educational status, there was more than one head of household listed, an individual was engaged in multiple primary activities, the quantity of crops and their byproducts produced, harvested, and sold not listed, the distance from the market and an individual\u2019s plot was not listed, the number of weeks, days per week, and hours per day an individual engaged in fishery activity was not recorded, the species and quantity of fish caught, bought, sold, or traded was not listed, etc). When it was determined that these values were the result of data-entry error, the values were corrected. In addition, cases deemed to reflect obvious enumerator error were also corrected in\nthis cleaning process. The majority of such cases involved the use of incorrect measurement units, e.g. recording grams as kilograms or vice versa."},"analysis_info":{"response_rate":"The total sample size for the second round of the NPS has a total sample size of 3924 households. This represents 3168 round one households, a re-interview rate of over 97 percent. In addition, of the 10,420 eligible adults (over age 15 in 2010), 9,338 were re-interviewed, a re-interview rate of approximately 90 percent"}},"data_access":{"dataset_use":{"contact":[{"name":"National Bureau of Statistics","affiliation":"","email":"dg@nbs.go.tz","uri":"www.nbs.go.tz"}],"cit_req":"National Bureau of Statistics (NBS) [Tanzania]. 2011. Tanzania National Panel Survey Report (NPS) - Wave 2, 2010 - 2011. Dar es Salaam, Tanzania: NBS. (www.nbs.go.tz)","conditions":"Tanzania NBS considered three levels of accessibility: \n\n1) Public use files, accessible by all\n2) Licensed datasets, accessible under certain conditions\n3) Datasets only accessible on location, for certain datasets\n\nThe dataset has been anonymized and is available as a Public Use Dataset. It is  accessible to all for statistical and research purposes only, under the following terms and conditions:\n1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the Nationa Bureau of Statistics, Tanzania. \n2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations. \n3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the National Bureau of Statistics. \n4. No attempt will be made to produce links among datasets provided by the NBS, or among data from the National Bureau of Statistics  and other datasets that could identify individuals or organizations. \n5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the National Bureau of Statistics will cite the source of data in accordance with the Citation Requirement provided with each dataset. \n6. An electronic copy of all reports and publications based on the requested data will be sent to the  National Bureau of Statistics\n\nThe original collector of the data, the National Bureau of Statistics, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such 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