MétaCan
Menu
Back to cohort

Something to Talk About: Re-thinking Conversations on Research Culture in Canadian Academic Libraries

2011· article· en· W2120032137 on OpenAlexaffvenueabout
Heidi Jacobs, Selinda Berg, Dayna Cornwall

Bibliographic record

VenuePartnership The Canadian Journal of Library and Information Practice and Research · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsScholarshipConversationContemplationSociologyPublic relationsPolitical scienceEngineering ethicsEpistemologyEngineering

Abstract

fetched live from OpenAlex

As Canadian academic librarians have experienced an increasing presence in faculty associations and unions, expectations of librarian scholarship and research have increased as well. However, literature from the past several decades on academic librarianship and scholarship focuses heavily on obstacles faced by librarians in their research endeavours, which suggests that the research environment at many academic libraries has stalled. Though many have called for the development of a research culture, little has been said regarding how the profession might go about encouraging this development, and conversations often become mired in the contemplation of obstacles. As a way to move forward, we suggest building upon pre-existing strengths by adopting the model of “intellectual communities” put forward by Walker et al. They describe four qualities necessary for strong “intellectual communities”: shared purpose; diverse and multigenerational community; flexible and forgiving community; and respectful and generous community. Although these qualities are often embedded within our libraries, they need to be made a conscious part of our research environment through reflection and conversation. Working toward strong research cultures requires that we focus less on obstacles and more on reflective and productive activities that build on our strengths.

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)0.021
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0040.000
Scholarly communication0.0000.019
Open science0.0010.000
Research integrity0.0000.005
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 head0.371
GPT teacher head0.517
Teacher spread0.147 · 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 designNot applicable
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

Citations7
Published2011
Admission routes3
Has abstractyes

Explore more

Same venuePartnership The Canadian Journal of Library and Information Practice and ResearchSame topicHealth Sciences Research and EducationFrench-language works237,207