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Record W2594585222 · doi:10.1002/bul2.2017.1720430310

Joint SIG/USE‐SIG/SI Research Symposium: Information Behavior in Workplaces

2017· article· en· W2594585222 on OpenAlexfundaboutno aff
Katriina Byström

Bibliographic record

VenueBulletin of the Association for Information Science and Technology · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsnot available
FundersUniversity of British ColumbiaUniversity of Kentucky
KeywordsWorkforceLibrary scienceJoint (building)Work (physics)Balance (ability)SociologyGerontologyOperations researchManagementPsychologyPolitical sciencePublic relationsEngineeringMedicineComputer scienceLaw

Abstract

fetched live from OpenAlex

EDITOR'S SUMMARY The 16th Annual Research Symposium for Special Interest Group/Information Needs, Seeking and Use (SIG/USE) was held in Copenhagen, Denmark. The focus of the symposium was information behavior and information practices as applicable to workplaces. As technology grows and shifts on a constant basis, so too must workplaces adapt how information is used and accessed. Newer generations in the workforce are expected to be able to learn many new skills, change careers several times and balance work life from home life with boundaries that are less clear than they used to be. Two presentations given by the 2014 and 2015 winners of the Elfreda A. Chatman Research Proposal Award started off the symposium. The 2016 winners of this award were announced by the awards committee chair, Wade Bishop, and included Karen Fisher of the University of Kentucky and Devon Greyson of the University of British Columbia, Canada.

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)0.016
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.007
Open science0.0020.001
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 head0.198
GPT teacher head0.425
Teacher spread0.227 · 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.

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

Citations0
Published2017
Admission routes2
Has abstractyes

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