Considering Knowledge Uptake within a Cycle of Transforming Data, Information, and Knowledge
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
Abstract Knowledge uptake, having decision makers assimilate the ideas of experts, is recognized as an important stimulus to bringing about policy change. This is particularly true in the realm of environmental policymaking, which is characterized by knowledge intensity, complexity, and multifaceted concerns. Using examples from an innovative watershed management organization, this article presents a heuristic for understanding how knowledge uptake occurs within a cycle of organizational reasoning. This cycle is driven by activities that transform data, information, and knowledge and that link specialists with decision makers. The heuristic can be used as a diagnostic tool to identify breaks in the transformation process that impede mandate fulfillment and impair capacity building. Lack of appreciation of the dynamic relationship between data, information and knowledge leads to mistimed and ineffective policy interventions that do not result in the hoped for progress in science intended to underpin policy advances.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it