Bibliographic record
Abstract
Institutionalization is a central yet elusive process in institution theory. While macro-institutionalization has been extensively studied, and studies of its micro-counterpart on the rise, efforts to promote a framework that bridges these two remain scarce. From a Peircean semiotic perspective, we theorize the process of institution emergence as changes in the triadic relations among Object, Representamen and Interpretant, associated with individual’s semiotic experiences nurtured by contextual information flows of distinctive nature and directions. Based on Peirce’s class of signs or semiotic categories, we offer a detailed semiotic model of institutionalization, from null institution to proto-institution then to institution, where the emergence is associated with the different semiotic categories into which the candidate institution evolves. We illustrate our framework with the proto-institutionalization of the red square, a visual-material artifact that has been mobilized repeatedly in the recent history of Québec, Canada and has been spreading beyond its national and geographical boundaries.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.054 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".