Swedish Biotech Smes: The Veiled Values in Online Networks
Bibliographic record
Abstract
This study considers the role of social networktheory in unveiling the hidden value in Internet networks in the Swedishbiotechnology industry. To value informal internet-based networks, socialnetwork analysis is used to identify key nodes in the network on the Internetfor small- to medium-sized enterprises (SMEs), using data from the Swedishbiotech industry. Data concerning the online networks of Swedish biotech SMEs (defined asenterprises with fewer than 100 employees) were gathered through: (1)identifying three different biotech SME company websites as the starting point;(2) recording all the hyperlinks referring to external websites; (3) visitingthose links back to the originating links; and (4) constructing a sociogram ofthis network. Prominence and structural hole analyses were used to determinethe most important networks and actors in the system. The findings show that networks can be constructed from the links betweenthe websites of actor firms. The findings also suggest the possibility of usingsocial network theory to identify the most prominent actors and to outline theentrepreneurial opportunities in whichthese identified actors can engage.(CBS)
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".