Bibliographic record
Abstract
Version:1.0 StartHTML:0000000167 EndHTML:0000001617 StartFragment:0000000457 EndFragment:0000001601 Digital Habitats: stewarding technology for communities by Wenger, White and Smith, has been out for two years and it has had numerous positive reviews. The book is well written, indeed, and it is extremely clear and enjoyable to read. The book focuses on the area where the interplay between technology and communities intersects, which the authors identify as “digital habitats”. In practical terms, a digital habitat is “the portion of a community that is enabled by a configuration of technologies” (p38). A digital habitat, like its biological counterpart, is a dynamic entity, which needs to adapt to environmental changes. It is thus important to determine its technological landscape and the space for maneuvering in it. The authors introduce the concept of “technology stewardship” to refer to the emerging practice of helping a community “choose, configure, and use technologies to best suit its needs” (p 24). These activities are carried out by certain members of the community, the “technology stewards”, who take a leadership role.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.073 | 0.029 |
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".