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Record W2561312713 · doi:10.18438/b8933q

National Differences in Perceived Benefit of Libraries May Be Due to Their Investments in Libraries, Library Supply, and Cultural Factors

2016· article· en· W2561312713 on OpenAlexvenueno aff
Ann Glusker

Bibliographic record

VenueEvidence Based Library and Information Practice · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsRespondentDescriptive statisticsDocumentationSample (material)PsychologyPopulationDemographyLibrary scienceMedical educationGeographySociologyStatisticsMedicinePolitical scienceMathematicsComputer science

Abstract

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A Review of: Vakkari, P., Aabø, S., Audunson, R., Huysmans, F, Kwon, N., Oomes, M., & Sin, S. (2016). Patterns of perceived public library outcomes in five countries. Journal of Documentation, 72(2), 342–361. http://dx.doi:org/10.1108/JD-08-2015-0103 Objective – To compare citizens' perceptions of the benefits of libraries in five culturally diverse countries. Design – Postal survey to a random stratified sample and web surveys (some with a sampling plan, some apparently not). Setting – Surveys were administered in Finland (by post), Norway, the Netherlands, the United States of America, and South Korea (online). Subjects – Selected or self-selected members of the general adult population in the specified countries who had used a public library within the past year. Methods – Surveys were administered and data were collected in each of the five countries. A dependent variable representing perceived outcomes was calculated from 19 outcome measures (related to life experiences). Within this, 4 indices were calculated from subsets of the 19 measures, relating to work, education, everyday activities, and leisure activities. Five independent variables were used: frequency of library use, number of services used, gender, age, and education level. Respondent country was also entered into analyses. Descriptive statistics and analysis of covariance results were presented. Main Results – It was noted that each country's sample was skewed in some way towards one or more of the variables of gender, age, and education, and some statistical corrections were employed. While patterns within countries are similar, library users from Finland, the United States of America, and South Korea reported higher levels of benefits overall. "Fun in reading" and "self-education" were the two outcomes with the highest scores by respondents. Higher numbers of visits and greater use of services may account for the higher perceived benefits in the three countries reporting them. In fact, these two factors appear to explain a substantial portion of the variance in perceptions of benefits between countries, meaning that between-country variation in library resources and supply plays a role in perception of benefit. There were varied rather than linear patterns of benefit reporting along age and education continua, with those at the lowest education levels deriving the most perceived benefits in all spheres. By gender, women derived fewer perceived benefits in the work sphere than men. Conclusions – There is variation across countries in the level of public library benefits reported, as well as variation across individual measures, creating different profiles of response by country. Even when respondent demographic characteristics and library usage are controlled for, country differences remain. These may be explained by the differences in investment in – and hence supply of – libraries by country, types of investment (e.g., according to the authors, Finland invests in services, Norway in collections, and the USA in staffing), and cultural factors such as the propensity of USA respondents to have a more extreme response style. Future research may profitably concentrate on policy contexts of libraries in each country. In the nineteenth century libraries provided social welfare services and in the twentieth they provided human rights through equitable access to information, so research should focus, by country, on what libraries will provide in the twenty-first century. Future studies might also address how differences in demographic patterns among respondents play out in benefit perceptions between countries.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.403
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.283
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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