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Record W2113587489 · doi:10.1002/meet.2014.14505101003

Boundary objects in information science research: An approach for explicating connections between collections, cultures and communities

2014· article· en· W2113587489 on OpenAlex
Isto Huvila, Theresa Dirndorfer Anderson, Eva Hourihan Jansen, Pamela J. McKenzie, Lynn Westbrook, Adam Worrall

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the American Society for Information Science and Technology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsVariety (cybernetics)Boundary (topology)Information scienceSociologyBoundary objectEpistemologyState (computer science)Data scienceSocial scienceComputer scienceEngineering ethicsLibrary scienceEngineeringMathematics

Abstract

fetched live from OpenAlex

ABSTRACT Boundary objects (BO) are abstract or physical artefacts that reside in the interfaces between organisations or groups of people. The concept of BO, introduced by Star and Griesemer in an article in 1989, has been used in a broad variety of studies in different research communities from management to computer science and different fields of information science. The aim of this panel, composed of experienced BO researchers, is to provide an overview of and introduction to the state of the art of information science research informed by the theory for the researchers and practitioners participating in the conference; to illustrate the variety of studies and contexts in which the notion of BOs can be found useful in explicating connections between collections, cultures and communities; and to push forward the state of the art of BO‐oriented information science research by discussing new empirical and practical areas of interest and the theory itself.

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.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0060.008
Scholarly communication0.0010.009
Open science0.0010.000
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 head0.060
GPT teacher head0.388
Teacher spread0.329 · 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