Communicative vs material actions: Instrumentality, sociality and comprehensibility
Bibliographic record
Abstract
There are several approaches that attempt to relate the action concept to information systems. There are approaches based on Activity Theory, Actor Network Theory, Organisational Semiotics and Language Action Perspective. Within the approaches of Organisational Semiotics and Language Action there is a great interest in the concepts of speech act and communicative action. In the communicative action theory of Habermas, there are fundamental distinctions made between communicative actions and material (instrumental) actions. Sociality and comprehensibility are associated with communicative actions and not with material actions. Instrumentality is associated with material actions and not with communicative actions. These characterisations are analysed and contested. Based on these analyses, an investigation of action types related to information systems has been pursued. The approach for Information System Actability has been used as a framework. Three different usage situations of information systems have been investigated and characterised: Interactive, automatic and consequential usage situations. An example of home care service is used as an illustration. The copyright of this paper belongs to the paper's authors. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage. Proceedings of the Sixth International Workshop on the Language-Action Perspective on Communication Modelling (LAP 2001) Montreal, Canada, July 21-22, 2001 (M. Schoop, J. Taylor, eds.) http://www-i5.informatik.rwth-aachen.de/conf/lap2001/ G. Goldkuhl 2 The Language-Action Perspective on Communication Modelling 2001 1
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.017 |
| Scholarly communication | 0.009 | 0.018 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".