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Record W7067512199

Library Trends 51 (4) Spring 2003: Research Questions for the Twenty-first Century

2008· article· en· W7067512199 on OpenAlexfundno aff

Bibliographic record

VenueIllinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
FundersCalifornia State University, FresnoSocial Sciences and Humanities Research Council of CanadaMemorial University of Newfoundland
KeywordsPublic healthHealth careNational libraryHealth informationQualitative researchSpring (device)Focus groupFocus (optics)
DOInot available

Abstract

fetched live from OpenAlex

Authors were told that the questions they chose could come from any area of librarianship and that some overlap between articles was expected.None of the authors followed the outline exactly, but each produced a thoughtful analysis of research needed in his or her area(s) of special interest.Two of the authors focus on research questions related to libraries serving areas of major national concern: education and health care.Delia Neuman's article on "Research in School Library Media for the Next Decade: Polishing the Diamond" describes what research is needed to advance the practice of school librarianship.Prudence W. Dalrymple's article on "Improving Health Care Through Information: Research Challenges for Health Sciences Librarians" explains how three major problems in health care delivery-quality, information access, and cost-lead to many questions for research by health care professionals, including librarians.Dalrymple raises the question of how to determine the impact of library service, a topic that is the entire focus of the article by Joan C. Durrance and Karen E. Fisher, "Determining How Libraries and Librarians Help."Durrance and Fisher pose that question for public libraries and strongly recommend context-sensitive qualitative methods as tools to answer it.Also focusing on public libraries is Virginia A. Walter's article on "Public Library Service to Children and Teens: A Research Agenda."Walter poses four key research questions and proposes a series of colloquia to set priorities for research in this area.Both public and academic libraries are mentioned in "Outcomes As- sessment in the Nehvorked Entironment: Research Questions, Issues, Considerations, and Moving Forward" by John Carlo Bertot and Charles R. McClure.These authors identify research topics related broadly to outcome assessment in a networked environment and propose a framework to relate that research to traditional evaluation.Both Carol Tenopir and Deanna B. Marcum focus on digital information in the networked environment.In her paper on "Electronic Publishing: Research Issues for Academic Librarians and Users," Tenopir raises three major questions and many related questions in the areas of digital resources and scholarly work, new models for scholarlyjournals, and librarians as intermediaries.Marcum's paper on "Research Questions for the Digital Era Library" raises similar questions about the use of digital resources, and also raises questions about preservation and about the education of future "librarians."Christine L. Borgman's article on "The Invisible Library: Paradox of the Global Information Infrastructure" begins with the premise that although libraries are essential to the nation's information infrastructure, they are often invisible to library users.The paper proposes four challenges that arise from this invisibility and suggests research questions arising from each of these challenges.Finally, Michael K. Buckland's "Five Grand Challenges for Library Research" is a short and stimulating essay on five Research in School Library Media for the Next Decade: Polishing the Diamond

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.043
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.011
Science and technology studies0.0130.020
Scholarly communication0.0350.034
Open science0.0030.009
Research integrity0.0160.009
Insufficient payload (model declined to judge)0.0330.007

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 head0.029
GPT teacher head0.265
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations0
Published2008
Admission routes1
Has abstractyes

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