The indicator 4a, developed in the context of the BAPS Logframe, measures the references in global summits to
statistical development and/or
This indicator measures progress towards the BAPS action area that aims to “ensure that outcomes of global summits and high-level forums specifically recognise the need for statistical capacity development”. See the BAPS document.
Definition of Global Summits
A first step towards identifying the data source for this indicator is the definition of global summit. A summit is a meeting between heads of governments (The Oxford Dictionary). For a summit to be global, it must bring together governments from around the world.
Following this definition, global summits can be characterised by exchanges between the participating governments. The events closest to this definition are the G20 summits that bring together governments from the 20 major economies. The G20, while closely fitting the concept of a global summit, can be criticised for not being truly global as discussions are driven by a rather select group of governments.
The approach proposed here is therefore to focus on intergovernmental organisations whose members are composed of the widest possible set of sovereign states. At the global level, these are the United Nations and (for each sectoral focus) and the FAO, IFAD, ILO, IMF, IMO, ITU, UNDP, UNESCO, UNIDO, WHO, World Bank, WMO, and WTO. These agencies bring together countries from all member states to discuss and set norms and policies.
2. Data sources
A. USE INFORMATION FROM UN AGENCIES TO SCREEN FOR GLOBAL SUMMITS
List of global summits
A natural second step is the identification of suitable outcome documents from UN specialised agencies that cover global summits and related discussions. One option is to draw up an exhaustive list of global summits. Immediate concerns with this approach are that this list would change annually and some of the largest summits are only organised biannually, which would introduce a lot of undesirable variation in such a measure.
Output documents from UN Agencies
The method proposed here is therefore to consider more frequent output documents from UN Specialised Agencies.
Use of direct output from UN agencies has two main advantages:
- First, it covers all relevant sectors at a global level.
- Second, and more crucially, this approach does not require the Secretariat to identify such events itself.
- Instead, the Secretariat can assume that agencies follow and report on topics discussed in the most relevant events in their sector.
B. COLLECT HIGH FREQUENCY TWITTER DATA
Another option is that their website content that can be captured through RSS feeds, for example. However, not every site has an active RSS feed and some (e.g. the World Bank) have dozens of feeds to subscribe to.
- It is thus proposed to use a standardised and frequent source of outcome documents: the official Twitter accounts of the agencies and their daily tweets, endorsements and retweets1.
- Tweets are particularly suitable because they cover the most relevant sectors and are published in an easily accessible format on a daily basis.
- The proposed indicator uses thus data extracted from the twitter timelines of these UN specialised agencies to measure the extent to which global summits include reference to statistical capacity development and data gaps.
- These tweets are currently restricted to 280 characters, making them easy to analyse.
The methodology proceeds in four steps.
1. In a first step, it extracts hashtags for the current year for the 15 UN Specialised Agencies as well as for 20 Statistical Agencies. The latter are taken from the website of the global partnership for sustainable development data (GPSDD). These include PARIS21, ODW, World Bank Data, FAO Stats, etc.
2. In a second step, the methodology creates a list of hashtags related to statistical development and data gaps. These are hashtags that occur at least three times2 more often in tweets of Statistical Agencies than they do for UN Specialised Agencies.
3. Next, we take the most frequent hashtags (the top 75%) and calculate the relative frequency of their occurrence for each of the 15 UN Specialised Agencies.
4. In the fourth step, we calculate the non-weighted average over these relative frequencies for the 15 agencies.
5. Finally, we show the trending history of top 6 hashtags used by those agencies.
D. Final Indicator and initial results
An initial analysis was undertaken based on 112 000 unique tweets containing a total of over 160 000 hashtags. The final indicator is the average over these relative frequencies for the 15 UN agencies. The relative frequency of tags related to statistical capacity development is currently at about 1,13%. It means that around 1% of all the hashtags used by all the UN agencies are related to statistical development and/or data gaps.
This methodology has several limitations.
a. Tweets are a non-representative data source made available by a private company. The methodology is therefore subject to biases and depends on continued access to the Twitter API, which may not be sustainable in the long term.
b. Difference between UN and country perspective: Although UN Specialised Agencies will by and large reflect the priorities of their member countries, they may not give a balanced view of the position of country’s heads of states.
c. Difference between frequency and impact of topics: Some topics may trend on Twitter and even induce herding behaviour among the agencies but do not make it on the agenda of high-level events.
d. Weighting of summits: Some summits do not really have an output but some others clearly have decisions. A future version of the methodology could aim to differentiate these and reflect this in the form of a weighting.
5. Next Steps and Conclusion
This indicator 4a provides a unique measure of references in global summits to statistical development and/or data gaps. It identifies hashtags related to statistical development and computes the relative frequency of these stats hashtags per UN agency. It allows therefore to observe the relative weight of each United Nation Specialised Agency in the total number of references to statistical development in global summits.
If approved by the Board, the Secretariat will continue the fully automated data collection for the indicator using the Twitter API and by the 2017 Board Meeting, will have established a baseline and determined a target for 2018.
As part of the implementation, the analysis will feed into the development of a freely accessible, online-based results monitoring instrument that allows users to track and browse outcomes of all global summits and high level forums.