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The UNESCO Institute for Statistics: How We Decide What Data To Collect Diane Stukel IASSIST 2003 Ottawa, Canada 30 May 2003.

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Presentation on theme: "The UNESCO Institute for Statistics: How We Decide What Data To Collect Diane Stukel IASSIST 2003 Ottawa, Canada 30 May 2003."— Presentation transcript:

1 The UNESCO Institute for Statistics: How We Decide What Data To Collect Diane Stukel IASSIST 2003 Ottawa, Canada 30 May 2003

2 l Semi-autonomous body whose mandate is to support statistical activities of UNESCO in areas of education, Science & Technology, Culture & Communications l Formally established in November 1999 with new director: Denise Lievesley l Statutes and financial arrangements agreed by UNESCO General Conference l Have our own governing board but receive a regular budget from UNESCO in a special account l Relocated in Montreal in September 2001 with mostly new staff UNESCO Institute for Statistics Who are we ?

3 l Collection and dissemination of cross-nationally comparable data on education, science & technology, culture & communications l Methodological, technical and conceptual statistical development; establishment and maintenance of international classifications l Analysis and interpretation of international data (often in partnership with others) l Statistical capacity building within countries for users and producers of data Functions of UIS

4 l Data should not be collected for their own sake but because they are needed for policy purposes l Countries should be fully involved in determining what data should be collected, with what frequency and how l Data are owned by countries and they should be assisted in making use of them l Response burden on countries should be minimised l Co-ordination with other international agencies is paramount l Methodology should be used which is appropriate to the circumstances l Data should be collected and used in a way that is culturally sensitive Principles underpinning the data collection Work of the UIS

5 l There are too few resources for data collection in many countries l Statistical staff may have inadequate expertise and they move posts frequently l Statisticians in line-ministries may be somewhat isolated l Statistical systems are often fragmented with little co-ordination between agencies l Some of the relevant data are collected outside the official statistical system eg by the private sector l There may be no protection against undue political pressure Barriers to collecting high quality policy relevant statistical data

6 Why Consult? To identify priority policy issues in order to define UIS programmes of work in education, S&T, C&C; To improve the visibility of UIS and promote our status as guardian of international database; To build and maintain a network of experts of both users and producers of our data; To give our stakeholders a voice - to let them know their opinion counts; To gain contextual knowledge of our Regions/Member States and their varying capacities;

7 Why Consult? To investigate the feasibility of data collections and to identify the gaps; To assess the need for statistical capacity building; To introduce survey vehicles, to encourage response and to facilitate the identification of problems or areas needing updating; To build an understanding of data quality issues with our existing vehicles and to develop a sense of how they can be addressed

8 Example 1: Culture Statistics Programme Up to recently, battery of six international surveys sent annually or biennially to 189 member states : museums, libraries (2), films and cinemas, book production, press  Need for renewal of UIS culture statistics programme!!  Current data collections limited to cultural institutions and cultural products  Need to consider broader spectrum of issues such as cultural producers, cultural participation, access to culture, benefits of culture, cultural diversity, …

9 Example 1: Culture Statistics Programme First step: “think tank” type symposium to solicit ideas on future collections of evidence-based policy-relevant data Papers/discussions from participants from both developed and developing world: 80 participants across 20 countries and all 5 continents involved Included broad spectrum of users from academic institutions, national government agencies, international organizations Symposium considered as first input to launching new culture statistics programme

10 Example 1: Culture Statistics Programme Strengths of Process: -Able to connect multitude of players at the same time; -Forged new relationships; -Initiated involvement in projects; -Increased visibility for UIS renewal of culture statistics programme Weaknesses of Process: -Difficult to identify appropriate players to represent opinions from all regions of the globe; -Concerns and attitudes often tended to be western; -Little discussion given to feasibility of suggested priority areas

11 Example 2: Science and Technology Statistics Programme Similar need for renewal as in culture statistics programme except further progressed in process Three phases to review process: A)International Expert Meeting, Montreal, April 2002 Objective: To help identify current and emerging science policy information needs involving policy makers from RICYT, ALECSO, OECD, Eurostat, etc Outcome: Background paper suggesting potential key areas and outlining currently available S&T indicators

12 Example 2: Science and Technology Statistics Programme B) Consultation of Member States and relevant institutions via questionnaire Objective:To ask broader audience to rank S&T policy issues C) International Meeting of Key S&T Data Users & Producers, Paris, March 2003 Objective: To discuss the results of the previous phases and to comment on proposed action lines for short, medium and long term strategies Since then first strategy document drafted - includes which indicators to collect + strategies for networking, publication, capacity building,… To be vetted through stakeholders electronically only, ultimately culminating in new S&T data collections

13 Example 2: Science and Technology Statistics Programme Strengths of Process: -Comprehensive and full-scale process -High visibility given to UIS -Users and producers given a voice in the process Weaknesses of Process: -Process heavy, resource intensive, time consuming -Tendency to give high priority to everything (questionnaire)

14 Example 3: Education Statistics Programme l Annual survey sent out: data sought on enrollment, teachers and finance for primary, secondary and tertiary levels l Annual workshops held in 11 regions of world: 4-5 days each including bilateral meetings l Objectives: Introduce new survey vehicle for the given year, improve quality of UIS education database by encouraging responses, identifying problems with answering questionnaire, building understanding of data quality issues, establishing contact with national statisticians,… l Education side to implement survey review and redesign in coming years…


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