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Record W2660520211

Impact Beyond Citation: An Introduction to Altmetrics

2014· article· en· W2660520211 on OpenAlexfundno aff
Cameron Neylon, Michelle Willmers, Thomas King

Bibliographic record

VenueOpen University of Cape Town (University of Cape Town) · 2014
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsAltmetricsCitationComputer scienceData scienceWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

A fundamental concern for higher education institutions worldwide is improving their efectiveness and efficiency. #is is often expressed as a need to maximise the "impact" of funded research. "Impact" is intended to mean the e!ects of research beyond the research community, and may include in$uence on policy, improvements in health and living standards, cultural enrichment or an improved environment. Di!erent forms of impact – and the framework by which impact is assessed and rewarded – should depend on the mission and goals of the institution. In a political environment that places high value on transparency, accountability and demonstrable return-from-investment, and with intensifying competition in global higher education, universities are under pressure to provide evidence of the value of services they provide. While the value of teaching services has been straightforward to measure, this has not been the case for research. #e commercial publishing sector provides citation-based analysis – the ISI Impact Factor – that is the dominant metric for research evaluation. But the ISI Impact Factor's methodology, equitability and ability to measure the range of scholarship have been criticised. The Altmetrics movement, a body of scholars that seeks to create tools allowing scholarship to be measured and tracked in novel ways, is challenging the ISI Impact Factor. The Scholarly Communication in Africa Programme investigated "alternative methodologies for a more Afrocentric approach to research evaluation".

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)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics, Open science, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0250.067
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0050.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.245
GPT teacher head0.446
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2014
Admission routes1
Has abstractyes

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