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Record W3009284560 · doi:10.11575/prism/37561

What is the Future of Libraries in Academic Research

2018· article· en· W3009284560 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOpen MIND · 2018
Typearticle
Languageen
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsnot available
FundersAndrew W. Mellon Foundation
KeywordsComputer science

Abstract

fetched live from OpenAlex

Research has changed, have libraries? Research at the University of Calgary has identified a constellation of services necessary to enable today's multidisciplinary and interdisciplinary research. This session will address the nature of evolving challenges and explore steps critical to the future of research libraries. With support from The Andrew W. Mellon Foundation, Libraries and Cultural Resources is seeking to instantiate a combination of services, expertise, and infrastructure through direct partnerships between library staff and scholars in a diversity of research endeavors. This research, enabled by competitive sub-grants, has ranged from providing real-time public access to arctic sensors to digitization and textual analysis of early science fiction writings to a repository for 3D scans of cultural heritage sites. This process will be examined from the perspective of the Project Coordinator, John Brosz, detailing the nature and results of direct participation by library staff in the various research projects and in the re-envisioning of library space as a constantly changing research lab. Suzanne Goopy, a social anthropologist and lead investigator in one of the funded projects, will illustrate her team's introduction of empathetic cultural mapping -- an approach that blends personal stories with population-level data. She will provide a researcher's perspective on how this experience has produced for her and her team a new understanding of the scope of library services and the opportunities for substantive collaboration. Tom Hickerson will address the critical importance of implementing a functional infrastructure and adopting a new model for the role of the library in campus research. He will describe the potential impact of this redefinition on libraries and on their continuing relevance in the research enterprise.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.006
Open science0.0040.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.094
GPT teacher head0.374
Teacher spread0.280 · 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