Knowledge‐system theory in society: Charting the growth of knowledge‐system models over a decade, 1994–2003
Bibliographic record
Abstract
Abstract The second half of the twentieth century saw the emergence of three knowledge‐system models: Mode 2 knowledge production, the Triple Helix, and Post‐Normal Science (PNS). Today, this emphasis on knowledge use is the focus of such important health movements as evidence‐based medicine. Building on the methodological work of Shinn (2002) and the theoretical work of Holzner and Marx (1979), we conducted a bibliometric study of the extent to which the three knowledge‐system models are used by researchers to frame problems of health‐knowledge use. By doing so, we reveal how these models fit into a larger knowledge system of health and evidence‐based decision making. The study results show clearly that although these knowledge models are extremely popular for contextualizing research, there is a distinct lack of emphasis on use of the models in knowledge utilization or evidence‐based medicine. We recommend using these models for further research in three specific dimensions of health systems analysis: (a) differences in language use, (b) transformative thinking about health‐knowledge functions, and (c) ethical analysis of institutional linkages.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.019 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.012 | 0.018 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".