Standardization of Network Technologies: Market Processes or the Result of Inter‐Firm Co‐operation?
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
As recent studies on the evolution of a technology indicate, the role of a standard, or dominant design, is highly significant in a number of contemporary industries such as computer, telecommunications and consumer electronics. Following Katz’ and Shapiro’s pioneering works (1985), our paper rationally evaluates the concepts and results developed over the past ten years in this field. It is grounded on a typology of two types of models: the first is based on users’ anticipatory behaviour, and the second, on the collaborative behaviour of existing firms. The article initially discusses the specificity of network technologies, then analyses market standardisation models, and finally, studies the different actors models. Our conclusion builds upon existing works in network technologies. We next propose a research agenda
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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