Bibliographic record
Abstract
It was a special moment. Non-profits were still figuring out the fax machine. No one had heard of the Internet. A few brave souls were stringing computers together, hanging modems and activists off the other end. The information — and the shifting political tide — were beginning to flow. News and passion trickled from the ANC headquarters in London to every nook and cranny of South Africa. Meetings were planned and new social movements dreamed over a few modems and a 286 in Toronto. Lobbying tactics, grand visions and messages home all emanated from a little computer room as thousands of environmentalists converged on Rio. At the center of all this was a band of computer activists calling themselves the Association for Progressive Communications (APC). The APC is a global coalition of nonprofit organizations who supply Internet content and connectivity services to civil society. APC was founded by a group of seven organizations who had all been providing e-mail and on-line discussion forums to non-profits and non-governmental organizations (NGOs) since the mid-1980s. This group included Alternex in Brazil, GreenNet in the UK, Nicarao in Nicaragua, IGC (PeaceNet and EcoNet) in the U.S., NordNet in Sweden, Pegasus in Australia and Web Networks in Canada. APC now includes 25 member networks located on six continents.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 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".