A critical narrative approach to openness: <scp>T</scp>he impact of open development on structural transformation
Bibliographic record
Abstract
Abstract Openness has become an important, all‐encompassing term denoting activities facilitated by sharing, using, producing, and redistributing information and communication resources within digital information systems. We compare theoretical advancements that emphasize processes and characteristics of openness with the limitations of extant approaches that have largely focused on improvements to productivity and efficiency. Based on Foucault and Bruner's ideas, this paper contributes a new critical narrative approach to understanding openness explicitly focused on structural transformation and power. The analysis focuses on the case of open development, examining 20 key studies based primarily on developing countries. The critical narrative approach unpacked the production of power/knowledge across actors, intentions, and outcomes of openness research and practice. We find that discursive formations are reliant on technocentric and normative ideals of researchers, leading to narratives of hypothetical outcomes that exclude marginalized perspectives. We propose hermeneutic composability and contesting normative narratives of openness as analytical techniques for an integrated, mutually constitutive conception of interactions between individuals, open artefacts, and open social praxis.
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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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.007 | 0.054 |
| Scholarly communication | 0.012 | 0.022 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".