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Record W1568498569 · doi:10.2307/40323939

Research Methods as a Core Competency

2003· article· en· W1568498569 on OpenAlexaboutno aff
Soyeon Park

Bibliographic record

VenueJournal of Education for Library and Information Science · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationWork (physics)Educational programCore competencyLibrary scienceInformation scienceMedical educationHigher educationSociologyPolitical scienceComputer scienceManagementEngineeringMedicine

Abstract

fetched live from OpenAlex

Research methods are not required by many library and information science (LIS) programs in the United States and Canada; in fact, only half of the ranked programs require such courses of master's of library science (MLS) students. Yet, at the same institutions as the LIS programs, research methods are required in science programs, most social science programs, master's in business administration (MBA) programs, and graduate social work programs. Accreditation standards in business and social work reinforce an individual program's need to require research methods. In graduate education programs, accrediting bodies do not require research methods courses and LIS can be defined-on this issue-as similar to education programs and, possibly, humanities programs. Research competency by MLS graduates accrues sustained benefits to the field. If MLS graduates are to be contributors and consumers of research, then LIS will need to require research methods courses of all students. If the LIS programs are reluctant to include research methods as a core course, then the American Library Association (ALA) may need to make this a requirement for accreditation.

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)0.248
metaresearch head score (Gemma)0.237
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.248
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2480.237
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.003
Science and technology studies0.0050.029
Scholarly communication0.0210.014
Open science0.0040.013
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0080.008

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 head0.084
GPT teacher head0.486
Teacher spread0.402 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations29
Published2003
Admission routes1
Has abstractyes

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