Information and Communication Technologies for Evaluation (ICT4Eval)
Abstract
This chapter offers several examples from institutions, ranging from international financial institutions to private-sector firms and international non-governmental organizations. The conference on Information and Communication Technology for Evaluation, organized by International Fund for Agricultural Development in 2017, aimed to identify ways in which technology could bridge the gaps in data for Sustainable Development Goals. Evaluations have historically depended on document reviews, observations and interviews during field visits for qualitative data. In the development sector, wireless devices are increasingly being used to collect monitoring and evaluation data. Evaluations can contribute to improving the quality of decision-making by providing timely feedback and rigorous evidence on effectiveness of development programmes. Geospatial tools have enhanced the Global Environment Facility evaluation team’s ability to undertake analysis efficiently and cost-effectively at project, national, global and ecologically meaningful scales. The challenge is to devise ways to use the strength of machine learning to improve causal inference and impact evaluation methods.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
There are about 8 million (74.9%) active social media users in Greece, and more than one fourth (25.8%) of Greeks use the Internet to buy tourism services.
“There are about 8 million (74.9%) active social media users in Greece [65], whereas more than one fourth (25.8%) of Greeks use the Internet to buy tourism services [66].”
From Push and Pull Travel Motivation: Segmentation of the Greek Market for Social Media Marketing in Tourism (2020) · cites this paper as [65]
Cites
Fine resolution mapping of population age-structures for health and development applications
Alegana, V. A., Atkinson, P. M., Pezzulo, C., Sorichetta, A., Weiss, D. J., Bird, T. J., zu Erbach-Schoenberg, E., & Tatem, A. J. (2015) · Journal of The Royal Society Interface · doi:10.1098/rsif.2015.0073 · Cited by 89 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Katsikari, C., Hatzithomas, L., Fotiadis, T., & Folinas, D. (2020) · Sustainability · doi:10.3390/su12114770 · Cited by 112 · see citing works
- Authors
- García, O. A., Pulkkinen, J., & Kotturi, P.
- Venue
- Information and Communication Technologies for Development Evaluation
- Publisher
- Routledge
- Published
- 2019-07-09
- Pages
- 27-75
- OpenAlex
- W2960553170
- Cited by
- 2
- References
- 1
- Citations by year
- 2023: 1 · 2020: 1
- FWCI
- 0.40
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
- Physical Sciences › Computer Science › Information Systems › ICT in Developing Communities
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- monitoring and evaluation, Sustainable Development Goals, data collection, wireless data collection, geotechnologies, machine learning, causal inference, impact evaluation, development programmes, International Fund for Agricultural Development, Global Environment Facility, decision-making
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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