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Record W1589479632 · doi:10.5555/1795234.1795285

Participatory tensions in developing a community learning network

2008· article· en· W1589479632 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

VenueParticipatory Design Conference · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCitizen journalismStakeholderEnthusiasmAgency (philosophy)Public relationsKnowledge managementSociologyBusinessPolitical scienceComputer scienceSocial scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This short paper reports on a study of St Christopher House (SCH), a community and social services agency that undertook an ambitious project to create a community learning network (CLN) based on a 'home-cooked' free/open source software (FOSS) content management system (CMS). The primary purpose of the CLN project was to provide adult learners with digital skills needed to secure employment in the knowledge-based economy. SCH also wanted to streamline administrative practices within the organization, reflecting an attempt to be inclusive and participatory. At the outset of the project there was an enormous investment of organizational energy, enthusiasm and participation. While this approach matched the various stakeholder expectations, the reality of transforming the CLN as an abstract ideal into practice produced internal tensions and stretched organizational capacities. This study examines the design and use of the CLN from the perspective of SCH staff in an effort to learn about how to reconcile conflicting organizational values and structures in the voluntary sector when undertaking ambitious participatory system development projects.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.560
GPT teacher head0.397
Teacher spread0.162 · 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