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Book (stand-alone)Conducting tablet-based field data collection with CSPro
A handbook
2020Also available in:
No results found.Conducting tablet-based field data collection with CSPro is a joint initiative of the Asian Development Bank and the Food and Agriculture Organization of the United Nations to support national statistics offices and line ministries to develop human capacities to conduct tablet-based field data collections for official statistics in the Asia and Pacific region for more robust, accurate and timely data. The adoption of tablet-based data collection methods, also referred to as Computer-assisted Personal Interviewing, is part of an overarching development in official statistics to adopt new cost-effective technologies to move from traditional pen-and-paper questionnaires to more cost-efficient, high quality and timely methods using electronic devices. This Handbook seeks to support this transition by providing step-by-step instruction and guidance to develop, test and run Computer Assisted Personal Interviewing field data collection using one of the free software’s currently available on the market – CSPro. -
Book (series)The use of students in surveying susbistence fisheries - a Pacific island case study. 2000
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No results found.This study tests the quality of subsistence fishery data returned by students in a field trial of a student census. 112 fourteen to eighteen year old students from one rural school on Upolus East Coast, Samoa, participated in the study. The students were all drawn from the second and third but last classes of the Samoan secondary education system (years 11and 12). Students were given a logbook containing one questionnaire on household specifics (socio-economic data), and seven daily log sheets, into which household seafood consumption, and fishing trip and catch specifics were recorded. Students recorded information for one week in the last full calendar week of August 1999. A household survey and a creel census were carried out in parallel, to serve as validating surveys, against which the data collected by the students were compared. It was found that there was weak overlap between socio-economic data collected by the students and data collected by the validating surveys, with studen ts reporting generally inflated values across the range of items sampled. It appears that this was not due to poor performance of students recording the information, but is likely to be due to the fact that the selected age group in this study does not embody a representative cross-section of the rural community (specifically in terms of household economics). Only 29 % of the logbook sections recording daily fishing activity (catch and trip information) were answered satisfactorily. This was in part attributed to the complexity of the daily log sheets and the length of the exercise. The pool of logbooks which had been completed satisfactorily however, yielded good results which closely matched indicators rendered by the validating surveys. -
Book (stand-alone)Measuring Individuals’ Rights to Land: An Integrated Approach to Data Collection for SDG Indicators 1.4.2 and 5.a.1 2019Land is a key economic resource inextricably linked to access to, use of and control over other economic and productive resources. Recognition of this, and the increasing stress on land from the world’s growing population and changing climate, has driven demand for strengthening tenure security for all. This created the need for a core set of land indicators that have national application and global comparability, which culminated in the inclusion of indicators 1.4.2 and 5.a.1 in the Sustainable Development Goals (SDGs) agenda. Having indicators on land ownership and rights in the SDG framework is an opportunity to routinely generate comparable, sex-disaggregated data to support evidence-based decision making on responsible land governance for sustainable development. The custodians of SDG indicators 1.4.2 (UN-Habitat and the World Bank) and 5.a.1 (FAO) have joined forces to develop a standardized and succinct survey instrument designed to collect the essential data for computation of both indicators simultaneously. As the data collection requirements for each indicator largely overlap, great gains in efficiency are possible by implementing a joint module in existing survey questionnaires. This document aims to facilitate the successful, efficient, and cross-country comparable data collection for computation of SDG indicators 1.4.2 and 5.a.1 in line with the methodologies approved by the IAEG-SDGs. The survey instrument discussed in this document was designed with an eye for the integration of essential questions for both indicators into existing survey instruments, with the possibility of stand-alone implementation. Use of the proposed module encourages the standardization of indicator definitions and data.
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