Mandate and gap mapping
Legal texts, regulator mandates and agency remits are coded against a technology's life cycle, so each stage shows who holds authority, who shares it, and where no institution is answerable.
GRF · Innovation Nexus
Policy science in innovation governance
Policy, institutional and decision science is the core method of this platform. It examines how mandates, funding rules, regulation and agreements shape what is invented, adopted and governed, and whether innovation programmes deliver the public value they claim.
01Contents
Policy science in innovation governance in five parts.
02Application
What policy, institutional and decision science does here.
Policy, institutional and decision science studies how public decisions are made, implemented and evaluated. It examines how institutions coordinate across sectors and levels of government when facing shared risks. In innovation, artificial intelligence and industry and robotics, policy science identifies governance gaps where responsibility for cross-sector risk is unclear. It supports the design of mandates, coordination mechanisms and accountability. The canonical description is on the STEM Commons.
Programme evaluation design
A mission or transfer programme is evaluated against a counterfactual such as rejected applicants or comparable regions, with outputs, outcomes and distribution kept apart and the logic model published.
Comparative regulatory analysis
Approaches to AI, sandboxes or invention ownership are compared across jurisdictions on legal basis, scope, enforcement and review, so a ministry sees the range of options before choosing.
03Monitor
Survey analysis.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Survey analysis
Innovation · Policy science in innovation · Run R-9377
Estimates stableGRF · Innovation Nexus
Estimates
robust standard errors
| Sandbox cohorts | 0.64 | 0.09 | [−0.3, 0.7] | Yes |
| Pilots with exit plan | −0.22 | 0.05 | [0.0, 0.7] | No |
| Licences transferred | 0.41 | 0.04 | [−0.5, 0.5] | Yes |
| Responsible innovation reviews | −0.15 | 0.14 | [−0.1, 0.3] | No |
Method card
- Method
- Policy, institutional and decision science
- Sample
- 7368 obs
- Design
- stratified, weighted
- Label
- MODELLED
Residuals by group
04Data
What the method consumes.
Datasets and records used by policy, institutional and decision science on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Legislation, regulations and authority gazettes | Mandates, obligations and legal bases | Published statistics |
| Funder programme rules and grant databases | Instruments, eligibility and awards | Published statistics |
| Evaluation and audit reports | Evidence of what programmes achieved | REPORTED |
| OECD.AI and STIP Compass policy records | Comparable national policy initiatives | DECLARED |
| Structured expert elicitation | Judgement where records are silent | ESTIMATED |
05Policy scenarios
Compare instruments: rules, incentives and information.
Three families of instruments side by side against the baseline, each with its own lag and adoption speed, under the coverage and compliance you set; effect sizes are teaching values to replace with evidence. Scenario: named assumptions about the future, not a forecast.
Controls
- Baseline trend of the outcome
- 2.0% a year
- Coverage of the instrument
- 70%
- Compliance
- 75%
- Effect size, against the teaching value
- 100%
- Years ahead
- 20 years
Readouts
- Largest reduction at the horizon
- Regulation
- Its reduction against the baseline
- 21%
Numbers, methods and sources
| Year | Baseline | Regulation | Economic incentive | Information and capacity |
|---|---|---|---|---|
| 0 | 100.0 | 99.5 | 98.8 | 99.1 |
| 1 | 102.0 | 101.2 | 100.1 | 99.8 |
| 2 | 104.0 | 102.5 | 101.1 | 99.9 |
| 3 | 106.1 | 103.5 | 101.6 | 100.0 |
| 4 | 108.2 | 103.7 | 101.8 | 100.7 |
| 5 | 110.4 | 103.2 | 101.7 | 102.1 |
| 6 | 112.6 | 102.0 | 101.6 | 103.9 |
| 7 | 114.9 | 100.4 | 101.6 | 105.9 |
| 8 | 117.2 | 99.2 | 102.1 | 108.0 |
| 9 | 119.5 | 98.6 | 102.9 | 110.1 |
| 10 | 121.9 | 98.9 | 104.2 | 112.3 |
| 11 | 124.3 | 99.7 | 105.7 | 114.5 |
| 12 | 126.8 | 101.1 | 107.4 | 116.8 |
| 13 | 129.4 | 102.7 | 109.4 | 119.2 |
| 14 | 131.9 | 104.5 | 111.4 | 121.6 |
| 15 | 134.6 | 106.5 | 113.5 | 124.0 |
| 16 | 137.3 | 108.5 | 115.7 | 126.5 |
| 17 | 140.0 | 110.7 | 118.0 | 129.0 |
| 18 | 142.8 | 112.9 | 120.4 | 131.6 |
| 19 | 145.7 | 115.1 | 122.8 | 134.2 |
| 20 | 148.6 | 117.4 | 125.2 | 136.9 |
Methods
- Tools of government Hood (1983), The Tools of Government, Macmillan
- Carrots, sticks and sermons Bemelmans-Videc, Rist and Vedung (1998), Transaction
- Diffusion of innovations Rogers (2003), Diffusion of Innovations, Free Press
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page's map can draw:
- Borders Natural Earth
- Cities Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Innovation Nexus in Foundry
- Tested at Innovation Nexus in Universe
- Codified in Open Infrastructure and Developers in Standards
- Published in Innovation Nexus in Reports
- Taught in Faculty of Technology and Digital Systems in Academy
06Validation
How results are checked.
Conclusions are tested through comparative cases, counterfactual evaluation and peer review. Implementation outcomes are monitored against stated objectives.
| Check | How it is done |
|---|---|
| Counterfactual design | Every impact claim names its comparison group and the assumptions that make the comparison valid |
| Source triangulation | Mandates coded from legal texts are checked against regulator practice and published decisions |
| Transferability statement | Lessons from one jurisdiction are reported with the institutional conditions they depended on |
| Independent review | Evaluation designs and comparative analyses are reviewed by experts outside the programme before publication |
Findings are often context specific and difficult to transfer. Political dynamics can override technically preferred options.
07Implementation
From mandate to evaluation, by pillar.
The steps an instrument takes from mandate to evaluation, each with the pillar that runs it, and the decisions that stay with the authority. Teaching model with stated illustrative values, not a prediction.
- Mandate and problem framing Competent authority (outside the programme)
A competent authority frames the problem and the mandate under its own rules. Howlett, Ramesh and Perl (2009) - Evidence and system model Foundry
The system is modelled with its feedbacks, data and stated limits. OECD (2014), principle 2 - Options appraised with scenarios Foundry
Instruments are compared under scenarios, with uncertainty shown. Hood (1983) - Exercise with stakeholders Universe
The options are tested in an exercise with those who would implement and bear them. OECD (2014), principle 3 - Standard or guidance drafted Nexus Standards
What works is codified as a standard or guidance, open to comment. Nexus Standards process - Decision by the authority Competent authority (outside the programme)
The authority decides, outside the programme, with the evidence on record. Howlett, Ramesh and Perl (2009) - Capacity and training Risk Academy
Those who implement are trained on the decided instrument and its data. Sendai Framework (2015), priority 2 - Monitoring and public report Reports
Indicators are published with sources, limits and corrections. OECD (2014), principle 5 - Evaluation and revision Nexus Standards
Results return to the standard and the model: the cycle closes. Howlett, Ramesh and Perl (2009)
Methods
- Policy cycle Howlett, Ramesh and Perl (2009), Studying Public Policy, Oxford University Press
- Governance of critical risks OECD (2014), Recommendation of the Council on the Governance of Critical Risks
- Layered drawing of directed graphs Sugiyama, Tagawa and Toda (1981), IEEE SMC 11
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Innovation Nexus in Foundry
- Tested at Innovation Nexus in Universe
- Codified in Open Infrastructure and Developers in Standards
- Published in Innovation Nexus in Reports
- Taught in Faculty of Technology and Digital Systems in Academy
09Instruments and commitments
How policy science in innovation governance is governed: instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Policy instrument matrix
The kinds of instrument available on policy science in innovation governance, by level of government and cooperation.
| Instrument type | Local | National | Regional | Global |
|---|---|---|---|---|
| Regulatory | Zoning, building codes | Laws, standards, licensing | Harmonised rules | Conventions and treaties |
| Economic | Local levies, grants | Budget lines, taxes, insurance schemes | Risk pools, regional funds | Financing mechanisms |
| Information | Local warnings | Disclosure, early warning, statistics | Data sharing arrangements | Global monitoring and reporting |
| Institutional | Local committees | Lead agencies, coordination councils | Regional bodies and secretariats | Multilateral mandates |
| Cooperative | Community agreements | Partnership compacts | Memoranda and joint programmes | Agreements and joint commitments |
Sendai Framework for Disaster Risk Reduction · UNDRRParis Agreement · UNFCCC2030 Agenda and the Sustainable Development Goals · United NationsInternational Health Regulations · WHO
10Stewardship
Who maintains the method.
Policy Nexus stewards policy, institutional and decision science for the Consortium and reviews how it is applied across platforms.
11Connected
Where this page leads across the Consortium.
12Questions
Questions and answers.
What are the limits of policy, institutional and decision science in this field?
Findings are often context specific and difficult to transfer. Political dynamics can override technically preferred options.
How are results checked?
Conclusions are tested through comparative cases, counterfactual evaluation and peer review. Implementation outcomes are monitored against stated objectives.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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