A multi-disciplinary approach to policy transfer research: geographies, assemblages, mobilities and mutations
Bibliographic record
Abstract
This paper outlines an approach to the global circulation of policies/models. This ‘policy assemblage, mobilities and mutations’ approach has emerged in recent years, primarily through the work of geographers. It is both inspired by, and somewhat critical of, the policy transfer approach associated with work in political science. Our argument is that the focus of geographers on place, space and scale, coupled with an anthropological/sociological attention to ‘small p’ politics both within and beyond institutions of governance, offers a great deal to the analysis of how policy-making operates, how policies, policy models and policy knowledge/expertise circulate and how these mobilities shape places. In making this argument, we first briefly review the literatures in human geography and urban studies that lie behind the current interest in the mobilisation of policies. We then outline the key elements of the policy transfer approach that these geographers have drawn upon and critiqued. In the third and fourth sections we compare and contrast these elements with those of the burgeoning policy mobilities approach. We then turn to the example of the Business Improvement District policy, which has been moved from one country to another, one city to another, in the process becoming constructed as a ‘model’ of/for economic development. We conclude the paper by arguing for an on-going multi-disciplinary conversation about the global circulation of policies, one in which geographers are involved alongside those from other disciplines, such as anthropology, history, planning and sociology, as well as political science.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.009 | 0.077 |
| Scholarly communication | 0.021 | 0.031 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".