On Comparison of Mechanisms of Economic and Social Exchanges: The Times Model
Bibliographic record
Abstract
An e-market system is a concrete implementation of a market institution; it embeds one or more exchange mechanisms. The mechanisms are – from the economic point of view – disembodied objects (models and procedures) which control access to and regulate execution of transactions. E-market systems are also information systems which are information and communication technologies artifacts. They interact with their users; have different features and tools for searching, processing and displaying information. This work puts forward an argument that the study of e-markets must incorporate both the behavioural economic as well as the information systems perspectives. To this end the paper proposes a conceptual framework that integrates the two. This framework is used to formulate a model, which incorporates the essential features of exchange mechanisms, as well as their implementations as IS artefacts. The focus of attention is on two classes of mechanisms, namely auctions and negotiations. They both may serve the same purpose and their various types have been embedded in many e-market systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.009 | 0.023 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".