Value Creation and Socioeconomic Inclusion in South African Maker Communities
Bibliographic record
Abstract
In socioeconomic environments affected by high and persistent income inequalities and unemployment, there is a need for participative approaches to innovation in support of socioeconomic inclusion. This article explores the features of collective action, in support of socioeconomic inclusion, identified in South African maker communities. Drawing on data from interviews with participants in seven maker communities, the study explores the kinds of value that participants experience through being part of these communities. Value creation is assessed in terms of the five overlapping cycles of value that Wenger et al. (2011) propose are present in successful communities and networks: immediate value, potential value, applied value, realised value, and reframing value. The study finds that all five value cycles are present in the experiences expressed by the South African maker community participants. The value is found to be particularly pronounced in the immediate value and applied value cycles. In respect of socioeconomic inclusion, the findings point to strong currents of social inclusion in the immediate value cycle, and strong elements of both social and economic inclusion in the applied value, realised value, and reframing value cycles.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".