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Record W1514941560 · doi:10.19173/irrodl.v9i1.532

Designing the Undesignable: Social software and control

2008· article· en· W1514941560 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 · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceSoftwareControl (management)Social softwareEducational technologySocial controlSociologyMultimediaHuman–computer interactionWorld Wide WebSocial sciencePedagogyArtificial intelligence

Abstract

fetched live from OpenAlex

Social software, such as blogs, wikis, tagging systems and collaborative filters, treats the group as a first-class object within the system. Drawing from theories of transactional distance and control, this paper proposes a model of e-learning that extends traditional concepts of learner-teacher-content interactions to include these emergent properties of the group. It suggests that this feature of social software can facilitate an approach to elearning that is qualitatively different from and capable of significantly augmenting traditional methods, with especial benefits for lifelong learners and those outside institutional boundaries. The paper goes on to explore some of the dangers and issues that need to be addressed in order for this new model to fulfill its promise, and to suggest a framework of principles to be used by designers of educationally-oriented social software.

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)0.007
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.821
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.131
GPT teacher head0.472
Teacher spread0.341 · 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