Functional Systems as Metric Forms and Institutions as Non-metric Forms: A Neo-Luhmannian Approach
Bibliographic record
Abstract
The article develops a new pair of fundamental concepts – metric and nonmetric – by exploiting the contrast between systems theory and neo-institutionalism. Borrowed from Manuel DeLanda, the concepts aims at describing the properties of social forms arising in a crowd of individuals functioning as a medium of communication. It is argued that neo-institutionalism privileges nonmetric forms. The crowd is rearranged into distinct groups just like space can be divided into topological zones. Individuals in the crowd take their identity from the group they are in: actor or non-actor, rational or non-rational, etc. By opposition, systems theory emphasizes metric forms as in the case of the functional systems of modern society analyzed by Niklas Luhmann. Each metric form is based on a signal activated by the circulation of individuals inside the crowd and thus creating a modulating flow. Metric forms are not tied to specific individuals. For the flow to go on, it is not necessary for the same individuals who once triggered the signal in the past to return and trigger it again. Anyone will do! Metric forms are truly different from their nonmetric counterparts since they do not categorize individuals by grouping them (or group individuals by categorizing them). JEL: B5, Y8
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.025 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".