Bibliographic record
Abstract
A six‐stage model was developed to conceptualize the evolutionary process for policy networks, using the 20‐year evolution of the Canadian Electronic Funds Transfer System/Point Of Sale (EFTS/POS) policy network as an example. A content analysis of 231 policy documents was used to create individual case studies of 16 stakeholders. These cases were vetted with respective stakeholders and then amalgamated into one large, chronological case study. These attribute data were converted to relational data, in the form of 51 matrices and four sets of sociograms, and then analyzed using network analysis. The results (a) show that, with some variation, the model provides a reliable map of the evolution of policy networks and (b) confirm that network analysis captures the attributes and properties of the relational dynamics inherent in stakeholder interactions during the development of policy. This augments the traditional approach of capturing the properties of actors, organizations or policy.
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How this classification was reachedexpand
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 | 0.017 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".