MétaCan
Menu
Back to cohort
Record W2538475594 · doi:10.5703/1288284316284

Effect of Library Advocacy on Mendeley User Adoption and Productivity

2016· article· en· W2538475594 on OpenAlexaff
Yath Ithayakumar, Helen B. Josephine

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicAcademic Writing and Publishing
Canadian institutionsPurdue Pharma (Canada)York University
Fundersnot available
KeywordsReading (process)Computer scienceProductivityPublishingWorld Wide WebKnowledge management

Abstract

fetched live from OpenAlex

Millions of researchers and students currently use Mendeley.com, a free reference manager and one of the largest academic collaboration networks, to support them in reading, writing, collaboration, and publishing processes. Mendeley is an easy‐to‐use reference management tool with only self‐help online tools available for researchers. However, in the last two years, with its integration with Elsevier, it has made available more varied support resources for new users. It is widely believed to be more effective to provide structured support for early career researchers versus just‐in‐time support for seasoned researchers; and structured support for STEM disciplines versus just‐in‐time for non‐STEM disciplines. This study first defines the baseline differences in user adoption and productivity rates between different disciplines (STEM versus non‐STEM users) and academic statuses (undergraduates, graduates, post‐docs, professors). Then, by applying different library resources (in‐person training sessions, help aid, tutorial video, and on demand support) in selected US institutions, this project attempts to understand the effects of different support resources to eventual user adoption and productivity.

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)0.000
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 score0.827
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.013
GPT teacher head0.217
Teacher spread0.204 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicAcademic Writing and PublishingFrench-language works237,207