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Record W1606519491 · doi:10.19173/irrodl.v16i1.2008

Open informational ecosystems: The missing link for sharing resources for education

2015· article· en· W1606519491 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2015
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
Fundersnot available
KeywordsOpen educational resourcesOpen educationKnowledge managementEcosystemComputer scienceEducational resourcesOpen learningBusinessWorld Wide WebEcologyTeaching methodSociology

Abstract

fetched live from OpenAlex

Open educational resources are not available “as such”. Their provision relies on a technological infrastructure of related services that can be described as an informational ecosystem. A closed informational ecosystem keeps educational resources within its boundary. An open informational ecosystem relies on the concurrence of independent stakeholders that jointly provide (meta-) information also beyond its boundaries. Mechanisms of open informational ecosystems are described and how they contribute to the delivery of educational resources and to opening education. The paper describes the case of the German Bildungsserver that aims at establishing a federated network of providers of open and closed educational resources. It points out that the design of (inter-)national informational ecosystems has a major influence on the future of open educational resources in education.

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)0.014
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0040.002
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 head0.151
GPT teacher head0.469
Teacher spread0.318 · 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