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Record W4211143510 · doi:10.47657/3015

Communication Skills of Library Staff: A Cognitive Study of Turks Using Library Services in Canada

2021· article· en· W4211143510 on OpenAlexaboutno aff
Elif ŞEŞEN, Yasin Şeşen, Harun Şeşen

Bibliographic record

VenuePakistan Journal of Information Management and Libraries · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismThematic analysisService (business)Public relationsImmigrationSociologyPolitical scienceLibrary scienceSocial sciencePedagogyQualitative researchBusinessComputer scienceMarketing

Abstract

fetched live from OpenAlex

Throughout the historical ages, migration movements have occurred due to different reasons such as wars, internal disturbances, environmental disasters, economic depressions, technological developments, and education. Efficient integration of individuals into society as a result of migration depends on the development of a multicultural perspective. Libraries are among the leading institutions today in terms of recognizing different cultures. Libraries serve everyone in society without any discrimination. In multicultural societies, immigrants can quickly and easily access all kinds of information they need from cultural libraries and information centers so that they can adapt to their new places and get equal service in cultural and social fields. For instance Canada, which is an example of a multicultural society, people who have been in the country were interviewed in the study aiming to evaluate the communication skills of staff working in library services. The data obtained with the semi-structured interview technique were subjected to thematic analysis. As a result of the analysis, a total of seven sub-themes were determined with two themes, ‘Library Services' and ‘Communication Skills'.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.007
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 head0.009
GPT teacher head0.249
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2021
Admission routes1
Has abstractyes

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Same venuePakistan Journal of Information Management and LibrariesSame topicSocioeconomic Development in MENAFrench-language works237,207