Research methods as bridging devices: path and context mapping in governance
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate the potential, both analytically and practically, of understanding research methods as bridging devices. Methods can bridge theory and empirics, but it is argued that they can perform several bridging functions: between theory and praxis, between analysis and strategy and between past and future. The focus is on those forms of bridging relevant for understanding and effectuating change in governance, at community level and at the scale of organizations. Design/methodology/approach The paper develops a perspective on methods as bridging devices. It uses the newly minted methods of governance path and context mapping as a case study. These methods conceptually derive from evolutionary governance theory (EGT) and were developed and tested in Canadian empirical research. The case helps to develop insight in features, forms and limitations of methods as bridging devices in governance research and practice. The authors then use the case to further develop the initial concept of bridging more generally, emphasizing the shifting balance between methods as bridging and creating boundaries. Findings Both the case study and the theoretical analysis underline the necessary imperfection of any method as bridging device. The authors affirm the potential of method to perform different bridging functions at the same time, while revealing clear tradeoffs in each role. Tradeoffs occur with adapted versions of the method producing new strengths and weaknesses in new contexts. In each of the forms of bridging involved neither side can be reduced to the other, so a gap always remains. It is demonstrated that the practice of bridging through method in governance is greatly helped when methods are flexibly deployed in ongoing processes of bricolage, nesting and modification. Governance enables the continuous production of new framing devices and other methods. Originality/value The idea of methods as bridging devices is new, and can assist the development of a broader understanding of the various forms and functions of research methods. Moreover, it helps to discern roles of research methods in the functioning of governance. The context of governance helps to recognize the multi-functionality of research methods, and their transformation in a context of pressured decision-making. Moreover, this approach contributes to the understanding of governance as adumbrated by EGT.
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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 | 0.091 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.006 | 0.060 |
| Scholarly communication | 0.019 | 0.035 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".