Bibliographic record
Abstract
The diffusion of digital information and communication technologies (DICT) is strongly supported by many countries of the world. Today, as well as in the past, new technologies are charged with high expectations, but at a closer look one can see that these expectations then are very different from now. Today they depend on the various interests of different groups of people. Globally acting enterprises see DICT as essential stra-tegic instruments in gaining competitive power; some governments hope to reach military hegemony, others to control terrorism and crime, while grass root movements expect to become more influential on some aspects of society. The paper identifies and analyses basic tendencies which promote the various hopes: the effects of DICT on reducing production and transaction costs, and the possibility to transform information goods into marketable services or commodities. The final part of the paper is devoted to a few examples of how the potential of DICT can be used for social improvements.
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 | 0.020 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.068 |
| Scholarly communication | 0.021 | 0.017 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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".