Bibliographic record
Abstract
Purpose The authors aim to apply a collectivist theoretical framework to the study of human information behaviour and the construction of meaning in a knitting group held in a branch of a large Canadian (Ontario) public library. Design/methodology/approach The research design was naturalistic and consisted of active participant observation of five knitting group sessions and semi‐structured interviews with 12 group members. Field notes were taken, and both observations and interviews were audio taped and transcribed. Field notes and transcripts were coded qualitatively. Findings Information practices and contextual factors are mutually constitutive. The location of the circle in a public library, the physical characteristics of the act of knitting, and the social meanings of the activities taking place within the group, including the significance of gender and caring, are integrally linked to HIB in this setting. Findings are described verbally and illustrated through a model. Research limitations/implications This study applies collectivist understandings to enrich concepts such as the “information ground” that have previously been studied largely from constructivist perspectives. As a small‐scale naturalistic study, results are context‐specific and must be applied tentatively. Practical implications This study provides an example of how programs in public libraries can provide opportunities for information behaviour and the construction of meaning for members of the community. Originality/value This study contributes a collectivist approach to research on everyday‐life information seeking and on the library as a place.
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 | 0.025 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.018 | 0.016 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.038 | 0.022 |
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".