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Record W4396982962 · doi:10.69520/jipe.v5i.163

Importance of Research Knowledge Dissemination

2023· article· en· W4396982962 on OpenAlexaff
Melanie Spence-Ariemma

Bibliographic record

VenueJournal of innovation in polytechnic education. · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsUniversity of Guelph-Humber
Fundersnot available
KeywordsInformation DisseminationKnowledge managementComputer sciencePsychologyWorld Wide Web

Abstract

fetched live from OpenAlex

An integral component of any research project is the dissemination of the findings.Sharing the results of a study helps to ensure the benefits of the study are passed on to others.This could mean positive economic, political, and social impact, advancing innovation, increasing visibility on an issue, and/or solving a complex problem.It is important that the benefits of a study are passed on to others.Finally, results can also cultivate research partnerships, promote future multidisciplinary research and be a conduit to promote new learning.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.312
metaresearch head score (Gemma)0.591
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.980
Threshold uncertainty score0.848

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3120.591
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0090.006
Science and technology studies0.0050.006
Scholarly communication0.0200.021
Open science0.0030.011
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.0150.006

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 head0.087
GPT teacher head0.482
Teacher spread0.395 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2023
Admission routes1
Has abstractyes

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