Bibliographic record
Abstract
A new set of conditions for healthy growth and adaptation is emerging for 21st century communities. This book has sought to explain what some of these conditions are, and to advise forward-thinking community leaders and stakeholders about how to take advantage of broadband bi-directional telecommunications to assure a better future for all. The high-speed Internet has given individuals, institutions and businesses ways to more efficiently connect and collaborate with one another, locally and globally. With pervasive digital networks in place, the economics of access, innovation and distribution have undergone radical transformation. The costs continue to drop throughout the value chain of products and services. The instruments of digital product, service and content creation that only a century ago were in the hands of governments, and only a decade ago were in the hands of big business, are now in the hands of local entrepreneurs and citizens as well. Anyone with a personal computer can now be a publisher, and anyone with an Internet connection can be a producer, marketer and distributor. Ordinary citizens who once thought of themselves only as consumers of other people’s products can now create their own content and build applications that can be—and are being—sold and adopted globally as well as locally. The democratization of the tools of content and service production and the collaborative networks that make information exchange more efficient and productive allow for more prosperous communities.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.235 | 0.097 |
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".