Conceptions of Everyday Life in Information Science
Bibliographic record
Abstract
ABSTRACT This panel examines conceptions of everyday life in Information Science. Several theories about everyday life and its information phenomena will be reviewed and analyzed for their origins, distinctions, and divergent claims. Four expert panelists who have published on these matters will encapsulate their ideas, and there will be a video interlude, as well. By design, the panel Agenda features short opening statements, leaving 40 minutes to discuss: How do existing notions of everyday life within Information Science bring information into focus in different ways? Are informational conceptions of everyday life adequate or wanting of critical re‐examination? In keeping with ASIS&T's multiperspective community, inputs will be sought from students, practitioners, first‐time conference attendees, and other groups, in turn. If, as Marcia J. Bates claims, we are “…always looking for the red thread of information in the social texture of people's lives” (1999, p. 1048) then we need to individually and collectively reflect on the nature of everyday life.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.016 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".