“Connections above and beyond”: Information, translation, and community boundaries in LibraryThing and Goodreads
Bibliographic record
Abstract
The connections and contexts surrounding information shared in social settings must be accounted for, and this is particularly true for online communities that are information‐centric. This article presents a mixed‐methods study of LibraryThing and Goodreads, which have characteristics of information‐centric online communities and social digital libraries, with attention to their roles as boundary objects, users' information values, and information behavior, and other boundaries and boundary objects at play. Content analysis of messages, a survey of users, and qualitative interviews show LibraryThing and Goodreads help establish community and organizational structure; support sharing of information values; and facilitate the building and maintenance of social ties. Translation of meanings and understandings within and between communities is a key activity in these roles. Online communities and social digital libraries should highlight translation processes and resources; provide user profiles and off‐topic spaces and encourage their use; take a sociotechnical approach to tailor technology and community features to the right audiences; and facilitate the establishment of shared structure, values, and ties and the work of boundary spanners. Further implications exist for research on and theorizing of information‐centric online communities, boundaries, and boundary objects as part of the sociotechnical infrastructure surrounding online information sharing.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Scholarly communication Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.026 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".