Analysing use of evidence in public policymaking processes
A theory-grounded content analysis methodology
Bibliographic Data
| ID | 12888751 |
|---|---|
| Authors | Itzhak Yanovitzky (0000-0001-6366-8006, Rutgers, the State University of New Jersey, corresponding author), Matthew S Weber (0000-0003-3880-9131, Rutgers, the State University of New Jersey) |
| Year | 2018 |
| Volume | 16 |
| Issue | 1 |
| Pages | 65-82 |
| Publication date | 2018-11-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Evidence & Policy (JOURNAL) |
| Journal identifiers | ISSN: 1744-2648 • E-ISSN: 1744-2656 |
| Publisher | Policy Press (PUBLISHER • GB) |
| DOI | 10.1332/174426418x15378680726175 |
| OpenAlex | W2899037114 |
| Language | EN |
| Citations received | 15 |
| References cited | 27 |
A broad range of methodologies is routinely employed to track and analyse use of research evidence in public policymaking. However, available methods and tools are mostly equipped to track ‘evidence’ but are less equipped to capture and represent ‘use’ of evidence. In particular, existing methods overlook policymakers’ frequent use of evidence for political persuasion and bargaining. Drawing on established theories and research tools from the field of persuasive communication, we developed a content analysis instrument for tracking and analysing policymakers’ use of evidence based on the information contained in policy documents. We provide a specific example of applying this tool and demonstrate how it may be used to generate rich and nuanced insights regarding the scope, nature, and timing of policymakers’ evidence use at different levels and phases of the public policymaking process. We conclude with a discussion of potential strengths and limitations and offer recommendations regarding the optimal application of this methodology
Content analysis · Data science · Economics · Evidence-based policy · Field (mathematics · Management science · Persuasion · Political science · Process (computing · Public policy · Scope (computer science · Social science · Sociology · Computer Science · Policy Transfer and Learning · Psychology · Public Policy and Administration Research · Social Media and Politics · Social Psychology
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Exploring the mental health education policies of Chinese college students
Quantitative evaluation of China's disaster relief policies
Framing with facts
Race-Based Trauma and Treatment Outcomes
Sentiment analysis as tool for gender mainstreaming in slum rehabilitation housing management in Mumbai, India
Patterns of evidence use in Nigerian policymaking
Can we trust that CBT-based batterer intervention programmes are effective?—Use of evidence for the treatment of IPV offenders in the prison and probation service
The extent of use of surveys in policymaking
Knowledge Utilisation Analysis
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Key achievements of New South Wales local government Disability Inclusion Action Plans in the era of inclusion policy and planning
From Enthusiasm to Concern and From Top-Down to Bottom-Up
Use of research evidence in the policy domain
Content analysis
Mass communication and society
Rethinking higher education and its relationship with social inequalities
Techniques and applications for sentiment analysis
Validation of Database Search Terms for Content Analysis
The Framing of Decisions and the Psychology of Choice
Agendas, alternatives, and public policies
The End of Framing as we Know it … and the Future of Media Effects
Measuring use of research evidence in public health policy
Measuring research influence on drug policy
Answering the Call for a Standard Reliability Measure for Coding Data
Evidence-Based Policymaking
The value of words
Document Analysis as a Qualitative Research Method
Measuring Use of Research Evidence
Brokering the Research–Practice Gap
The Many Meanings of Research Utilization
Structure of conversational argument
The political functions of expert knowledge
Framing, Agenda Setting, and Priming
Ideas and Policy Change
Using Documents in Social Research
Tracking discourse and qualitative document analysis
The Meaning and Measure of Policy Metaphors
| Citations per year | 2.14 |
|---|---|
| Citation span | 2019 - 2026 (8) |
| Highly cited | No |