Results 61 to 70 of about 207,200 (261)
The anatomy of EU policy-making: Appointing the experts [PDF]
European Integration online Papers, 2013 At 38,000, the total number of staff at the European Commission is relatively small for a body representing half a billion citizens. Likewise, the 3,500 strong research and statistical team is modest in size given that it operates across the Directorates General and other services.
openaire +2 more sources
Retractions in Rheumatology: Trends, Causes, and Implications for Research Integrity
Arthritis Care &Research, EarlyView.Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley +1 more source
From insight network to open policy practice: practical experiences
Health Research Policy and Systems, 2020 Background Evidence-informed decision-making and better use of scientific information in societal decisions has been an area of development for decades but is still topical.
Jouni T. Tuomisto +2 more
doaj +1 more source
Arthritis Care &Research, EarlyView.Objective Systemic lupus erythematosus (SLE) is a heterogenous inflammatory condition with widely varying global prevalence estimates. The frequency of SLE in the general population of Australia has been reported to be notably lower than contemporary estimates in countries such as the United States or United Kingdom, at 19 to 39 per 100,000 as opposed ...
Lucinda Roper +7 more
wiley +1 more source
A területfejlesztési képzés egyes jellemzői a hazai felsőoktatásban a 2010-es évek elején (Some Features of Education of Regional Policy in Hungarian Higher Education in the Early 2010s) [PDF]
DETUROPE, 2014 This paper is based on the lectures held at the conference of the Hungarian Society of Regional Science (2013, Kaposvár, Section: „The knowledge of EU regional policy in higher education”) on the one hand, and on the other hand it is based on studies ...
Pál Szabó +4 more
doaj
Agent-Based Models as “Interested Amateurs”
Land, 2015 This paper proposes the use of agent-based models (ABMs) as “interested amateurs” in policy making, and uses the example of the SWAP model of soil and water conservation adoption to demonstrate the potential of this approach.
Peter George Johnson
doaj +1 more source
Think Tanks, ‘policy experts’ and ‘ideas for’ education policy making in Australia
The Australian Educational Researcher, 2015 This paper provides a case study of the Centre for Independent Studies (CIS) in Australia with a focus on its education policy work, specifically the report, School funding on a budget (SFoB). CIS is a conservative right wing advocacy think tank, established in 1976 in the aftermath of the Whitlam government's policy activism, framed by classical ...
openaire +5 more sources
Arthritis Care &Research, EarlyView.Objective Rheumatic and musculoskeletal diseases (RMDs) are leading causes of physical disability, necessitating support with activities of daily living. This study describes social care received by patients with RMDs in two disparate regions of England: Salford (urban) and Norfolk (rural).
Mehreen Somro +6 more
wiley +1 more source
Salient monetary policy decisions and non-experts’ trust in central banks
Entrepreneurial Business and Economics ReviewObjective: The objective of the article is to shed new light on the relationship between central bank communication and the trust monetary institutions can obtain from ordinary citizens via a comparison of the European Central Bank (ECB) with the ...
Maqsood Aslam +3 more
doaj +1 more source
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation
CoRR, 2019 We consider the problem of imitation learning from a finite set of expert trajectories, without access to reinforcement signals. The classical approach of extracting the expert's reward function via inverse reinforcement learning, followed by reinforcement learning is indirect and may be computationally expensive.
Wang, Ruohan +3 more
openaire +4 more sources