Bibliographic record
Abstract
Purpose Canada's aging population is expected to have an impact on all public institutions; for public libraries, the emergence of a large, multi‐generational user group of older adults challenges the current paradigm of services to seniors. The purpose of this paper is to report on the reflections of a small sample of baby boomers and how the public library‐as place contributes to their caring relationships with their elders. Design/methodology/approach This study examined a subset of baby boomer library patrons who are in caring relationships with elders. The study is theoretically framed by the ethic of care and emerging theories of library‐as‐place grounded in human geography and sociology. An instrumental case study of seven carers in an urban Canadian city was conducted, using long form interviews. Findings Findings suggest that while these baby boomer respondents value their libraries deeply, there is potential to create services and practices more attuned to the needs of older adults who are in relationships with elders. Research limitations/implications As a single case of a small sample of baby boomers, this study is limited by its size, scope and geography. The direct voices of the elders could not practically be incorporated into this study and should be considered in future research. Originality/value This study offers an alternate framework to library‐as‐place studies based on a specific profile of “older adult” library users. It examines the library needs and uses of a small but rapidly growing sector of many public library communities. Older adults can be seen by libraries as two distinct demographic groups – the very old (elders) and their younger peers (baby boomers).
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
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 | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".