“Mainstreaming” foresight program development in the public sector
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This paper aims to develop a framework for benchmarking the maturity of public sector foresight programs and outlines strategies that program managers can use to overcome obstacles to foresight program development in government. Design/methodology/approach The public sector foresight benchmarking framework is informed by a bibliometric analysis and comprehensive review of the literature on public sector foresight, as well as three rounds of semi-structured interviews conducted over the course of a collaborative 18-month project with a relatively young department-level foresight program at the government of an Organisation for Economic Co-operation and Development (OECD) country. The paper frames public sector organizations as “complex adaptive systems” and draws from other government initiatives that require fundamental organizational change, namely, “gender mainstreaming”. Findings Nascent or less mature programs tend to be output-focused and disconnected from the policy cycle, while more mature programs balance outputs and participation as they intervene strategically in the policy cycle. Foresight program development requires that managers simultaneously pursue change at three levels: technical, structural and cultural. Therefore, successful strategies are multi-dimensional, incremental and iterative. Originality/value The paper addresses two important gaps in the literature on public sector foresight programs by comprehensively describing the key attributes of mature and immature public sector foresight programs, and providing flexible, practical strategies for program development. The paper also pushes the boundaries of thinking about foresight by integrating insights from complexity theory and complexity-informed organizational change theory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it