Reflexive Zeit- und Raumkonstruktionen und die Rolle des Global Buzz auf Messeveranstaltungen
Bibliographic record
Abstract
Reflexive time-space constructions and the role of global buzz at trade fairs. International trade fairs bring together agents from all over the world and create temporary spaces for presentation and interaction. Within specific institutional settings, participants not only acquire knowledge through face-to-face communication with other agents, they also obtain information by observing and systematically monitoring other participants. This paper analyzes trade fairs from the perspective of time-geography as reflexive time-space constructions which enable economic interaction within well-defined, spatially and temporally bounded places. Temporary face-to-face contact and the physical co-presence of global communities at these events establish a particular information and communication ecology, referred to as global buzz. This paper aims to analyze the constituting components of global buzz and to dismantle the complexity of this phenomenon in a multi-dimensional way. Participants at international trade fairs benefit from intensified decentralized knowledge flows in the form of learning by interacting and learning by observation. As such, these events establish central nodes in the global political economy through which knowledge is created and exchanged at a distance.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".