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Information Seeking in Context: Results of Graduate Student Interviews

2013· article· en· W1896707274 on OpenAlexaffvenue
Marg Sloan, Kim McPhee

Bibliographic record

VenuePartnership The Canadian Journal of Library and Information Practice and Research · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsWestern University
Fundersnot available
KeywordsGraduate studentsContext (archaeology)Information seekingMedical educationPsychologyPlan (archaeology)Information literacyQualitative researchSociologyPedagogyLibrary scienceComputer scienceMedicine

Abstract

fetched live from OpenAlex

We conducted a qualitative research study examining the information seeking behaviours of Psychology, Sociology and Women’s Studies graduate students at a large research intensive university to determine how graduate students find information; the roles that faculty members, fellow graduate students and librarians play in the information search; and graduate students’ knowledge of information resources and services. The context of graduate student information seeking was uncovered through an analysis of the data using the trichotomy of people, place and information. Across the disciplines, Master’s students were more likely to ask for librarian assistance than PhD students. The interview findings will be used to improve librarian support to this user group via an instruction plan aimed at those graduate students most in need of librarian assistance: Master’s students. We recommend a series of several (e.g., approximately four to eight) strategically timed brief (e.g., ten-minute) sessions offered via a first-year mandatory research methods course. Sessions would introduce students to key resources, explain the role librarians can play in their research and advertise the office hours service. This enhanced librarian support will ensure that all new graduate students have a common information seeking knowledge base and that they understand the services offered by their liaison librarians. Most importantly, it places librarians in close proximity to graduate students providing opportunities to uncover and address their actual research needs. Future research will look at the effectiveness of this plan in supporting graduate students with their 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 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)0.023
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0090.007
Scholarly communication0.0040.004
Open science0.0020.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.109
GPT teacher head0.392
Teacher spread0.283 · 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 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

Citations28
Published2013
Admission routes2
Has abstractyes

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