Participatory tensions in developing a community learning network
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.079 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.020 | 0.036 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".