MétaCan
Menu
Back to cohort
Record W2105224295 · doi:10.22215/timreview/758

Overcoming Barriers to Collaboration in an Open Source Ecosystem

2014· article· en· W2105224295 on OpenAlexaffvenue
Derek Smith, Asrar Alshaikh, Rawan Bojan, Anish Kak, Mohammad Mehdi Gharaei Manesh

Bibliographic record

VenueTechnology Innovation Management Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsCarleton University
Fundersnot available
KeywordsDiversity (politics)Open sourceKnowledge managementBusinessComputer sciencePublic relationsPolitical scienceLaw

Abstract

fetched live from OpenAlex

IntroductionCollaboration is the act of working with another individual or grouping to create something. It involves working jointly and openly with others. When collaborators bring their own diverse skills and experience – and new perspectives – the potential for innovation is great. However, collaboration is far from easy, and the diversity that brings benefits to the

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)0.045
metaresearch head score (Gemma)0.087
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.087
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.006
Scholarly communication0.0120.014
Open science0.0020.011
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.031
GPT teacher head0.362
Teacher spread0.332 · 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 designQualitative
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

Citations9
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueTechnology Innovation Management ReviewSame topicKnowledge Management and SharingFrench-language works237,207