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Open Science Policy Discourse Analysis (Methodology: Analysing Public…
Open Science Policy Discourse Analysis
Introduction
OA was discursively captured by commercial publishers; became aligned w/ structures the movement was supposed to challenge. Our motivations: Is the same possibly happening for OS?
Background
: OS has multiple negotiated meanings at grassroots. Language increasing used in national & international policy. Some argue becoming an empty rhetoric tool.
Question:
What are the OS discourses within policy? Is OS discourse reinforcing or weakening multilayered domination & inequality schemes that pre-exist in international community and in science?
Tentative Claim:
We found.... suggests current narrative dominating the OS paradigm is reinforcing international and regional domination schemes that pre-exist in the scientific and education fields. Lose sight of other functions of equitable knowledge production & sharing practices - attending to social challenges, equipping citizens to access fundamental rights, amplifying needs of disenfranchised, vulnerable, marginalised communities
2. Theoretical Framework
: Epistemic Governance
Methodology:
Analysing Public Policy as Discourse. Framing Theory
Why discoursive framing? Concepts can constrain/facilitate future courses or policy based actions, particularly based on preceding social relations & instituional norms
Policies/frames hold power; statements of support from institutions which can dictate norms, shape how resources are channeled, people are mobilised.
Data analysis
Identifying definitions, key characteristic features, suggest possible consequences/implications of frames given geopolitical/economic contexts.
Data collection
- global open science policies. beneficiaries, definitions, incentives, practises
Limitations/Caveats
Citizen science project. Conventional search engine. Overlap of terms/ideas (OA, open data, open innovation, open gov).
Findings: Narratives of Open Science in policy Making
Open Science = Open Access & Open Data for Innovation
As broad umbrella term. Often interchangeable/overlapping w/ OD/OA.
Innovation
open data/infrastructure as path to innovation.
Improve capacity of businesses, SMEs, industry, to innovate & create higher value products
"promoting innovation through knowledge creation in
science & tech
(Japan)
Social innovation & Responsible Innovation (G7)
Infrastructure
Developing tools/services to enable open data.
Tools to enable citation principles (STM)
Interoperable infrastructure for data sharing.
Building on repositories. Globally networked and distributed open science infrastructure
Open Access
Via Gold, or delayed access version (STM)
General 'accessibility of scientific investigations' (Mexico)
OA by default (EOSC 007)
Open Data
FAIR principles
Data stewardship
Data management/data science
Open science stakeholders: mostly scientists, researchers, academics, then gov't, private sector.
But also some citizens
.
Engagement & participation of citizens
As passive consumers
As way to popularise science
As an agent who can shape science
OS as more 'inclusive'
Open Science = Regional/International Competitiveness.
Driver of social & economic growth. Economic value of knowledge. Help position countries given comparative advantage.
Cost-benefit, efficiency, productivity language
Increase efficiency and diffusion (Elsevier)
Improving efficiency & quality of research by reducing costs of data collection (CONYCIT quoting OECD)
Reduces cost of data storage, reduces costs of researchers in public sector (EOSC)
Supports European market effectiveness - global leading role.
But not all about competition
open science does not thrive on extreme competition. (Mallorca) essential to bring funding success rates back to position where Europe's best researchers can attract & maintain funding. Monopolisation/cartelisation of publication enterprises not compatible with Open Science
Governance and Funding
Open Science = Building global research infrastructures
Discussion