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Riding the crest of the altmetrics wave: How librarians can help prepare faculty for the next generation of research impact metrics

2013· preprint· en· 6 citations· W2949915600 on OpenAlex· 10.48550/arxiv.1305.3328

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Metaresearch, Science and technology studies
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: QualitativeConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.298
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.751
GPT teacher head0.398
Teacher spread
0.354 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

As scholars migrate into online spaces like Mendeley, blogs, Twitter, and more, they leave new traces of once-invisible interactions like reading, saving, discussing, and recommending. Observing these traces can inform new metrics of scholarly influence and impact -- so-called "altmetrics." Stakeholders in academia are beginning to discuss how and where altmetrics can be useful towards evaluating a researcher's academic contribution. As this interest grows, libraries are in a unique position to help support an informed dialog on campus. We suggest that librarians can provide this support in three main ways: informing emerging conversations with the latest research, supporting experimentation with emerging altmetrics tools, and engaging in early altmetrics education and outreach. We include examples and lists of resources to help librarians fill these roles.

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.

The record

Venue
arXiv (Cornell University)
Topic
Social Media in Health Education
Field
Social Sciences
Canadian institutions
ImpactOpenAlex
Funders
not available
Keywords
AltmetricsDialog boxOutreachComputer scienceWorld Wide WebReading (process)Political science
Has abstract in OpenAlex
yes