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Record W4378555298

Conducting international research in the library and information science field: challenges and approaches

2022· article· en· W4378555298 on OpenAlexaff
Krystyna K. Matusiak, Kawanna Bright, Debbie Schachter

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsLangara College
Fundersnot available
KeywordsField (mathematics)Data scienceLibrary scienceComputer sciencePolitical scienceMathematics
DOInot available

Abstract

fetched live from OpenAlex

International comparative research in the library and information science (LIS) field examines the processes and phenomena related to libraries and other information organizations and their users. with a focus on differences and similarities across countries or cultures. International research is challenging due to language barriers, ethical concerns, and the legacy of the colonial research model. This paper presents an international research project undertaken by members of the International Federation of Library Associations (IFLA) Library Theory and Research (LTR) Section which investigated the approaches to teaching research methods in LIS programs worldwide. The paper focuses on the project’s research design, on the research ethical issues and on the collection of multilingual data. It discusses the inherent challenges in conducting international research and outlines the approach to increasing the geographic and linguistic diversity of study respondents. The LTR research team adopted several strategies to recruit participants from multiple countries and collect data in three languages. The recruitment announcements were distributed throughout international and regional mailing lists in multiple languages. The survey instrument was translated from English to Spanish and French, and the interviews were conducted in English and Spanish. The authors also discuss the methodological advantages of mixed-methods design and the benefits and limitations of using surveys and interviews in international research.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.117
Open science0.0030.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.671
GPT teacher head0.596
Teacher spread0.075 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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