Comparative Study of Public Libraries in Commercial Centers: A Case Study of Iran and United Kingdom
Bibliographic record
Abstract
Purpose: The purpose of this research is to conduct a comparative study of public libraries in Jundishapur (Iran Mall, Iran) and those in Whitechapel and Edmonton Green (UK), examining their services, advantages, and characteristics within commercial centers.Methods: This applied study used a mixed approach with emphasis on content analysis. The research population included the mentioned libraries. Data were collected through semi-structured interviews in the Jundishapur Library (Iran Mall) and through content analysis of reports from Whitechapel and Edmonton Green. The comparison addressed services, target communities, collections, service delivery, buildings, equipment, and administration. Collected data were analyzed through coding, categorization, and consolidation following descriptive phenomenology. Reliability and validity were confirmed using Guba and Lincoln’s four criteria (credibility, dependability, confirmability, and transferability). In addition, interview questions were reviewed and validated by experts in information science.Results: The findings reveal that libraries located in commercial centers provide cultural, social, and economic benefits both for the libraries and the shopping malls. Each of the studied libraries demonstrates distinctive characteristics in terms of services, user communities, collections, and facilities.Conclusions: The presence of public libraries in shopping centers generates positive impacts, most notably increased footfall for commercial centers. Moreover, such libraries possess the potential to deliver specialized services aligned with the unique features of their parent organizations.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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, 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".