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Record W2074165261 · doi:10.1007/s10668-014-9528-7

Innovation through collaboration: scaling up solutions for sustainable development

2014· article· en· W2074165261 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironment Development and Sustainability · 2014
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsQueen's University
Fundersnot available
KeywordsSoftware deploymentSustainable developmentKnowledge managementComputer scienceCommonsInformation and Communications TechnologyService (business)Open source softwareSoftwareBusinessEngineering managementWorld Wide WebEngineeringSoftware engineeringPolitical scienceMarketing

Abstract

fetched live from OpenAlex

The open collaborative philosophy employed in the success of open source (OS) software can be applied to hardware design. Specifically, the development of OS appropriate technologies (OSAT) can improve sustainable development efforts worldwide. Yet, widespread OSAT use is far from ubiquitous. Given that lack of communication, access to information and poor collaboration are among the largest barriers to a more effective OSAT dissemination, this paper explores opportunities to overcome such obstacles using four techniques: (1) collaborative online platforms, (2) crowd-sourcing, (3) the concept of knowledge commons, and (4) enabled educational institutions through service learning and applied research. The results are analyzed, and conclusions are drawn that outline paths to higher multiuser collaboration for OSAT deployment.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.248
Teacher spread0.230 · 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