Bibliographic record
Abstract
This project develops the concept of sustainable information practice within the field of information science. The inquiry is grounded by data from a study of 2 ecovillages, intentional communities striving to ground their daily activities in a set of core values related to sustainability. Ethnographic methods employed for over 2 years resulted in data from hundreds of hours of participant observation, semistructured interviews with 22 community members, and a diverse collection of community images and texts. Analysis of the data highlights the tensions that arose and remained as community members experienced breakdowns between community values related to sustainability and their daily information practices. Contributions to the field of information science include the development of the concept of sustainable information practice, an analysis of why community members felt unable to adapt their information practices to better match community concepts of sustainability, and an assessment of the methodological challenges of information practice inquiry within a communal, nonwork environment. Most broadly, this work contributes to our larger understanding of the challenges faced by those attempting to identify and develop more sustainable information practices. In addition, findings from this investigation call into question previous claims that groups of individuals with strong value commitments can adapt their use of information tools to better support their values. In contrast, this work suggests that information practices can be particularly resilient to local, value‐based adaptation.
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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".