Knowledge management and administration depend on semiotic information systems
Bibliographic record
Abstract
Knowledge management and administration have been defined according to the symbol system hypothesis. This paper argues that they depend instead on semiotic information systems that entail an event-driven and dispositional user perspective. Semiotics as the theory of signs implies that information systems be designed as contextual knowledge and action support systems. This has behavioural, conceptual and technological implications and suggests that cognitive, ethical, methodological, organisational and technological criteria must be met if we are to replace traditional, un-assuring data, model, and information processing systems with those that can provide assurances to their users. Assurance is a transient attribute of information because what we know changes frequently and what we receive in terms of information may neither be believable nor true. To dispel doubts requires built-in assurances based on proper internal control systems, understood as meta-information systems, and re-assurances by such assurors as competent, ethical, and independent auditors.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.041 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".