Open Development SMITH, ELDER, EMDON From the Guest Editors1 Open Development: A New Theory for ICT4D2
Bibliographic record
Abstract
Open development refers to an emerging set of possibilities to catalyze positive change through “open ” information-networked activities in international development. While there is evidence to sup-port the observation that these changes could be coming, we are only now beginning to glimpse their potential for developing societies. Consequently, embedded in this theory are a high level research question and hypothesis. The research question asks how these information-networked activities work, in what circumstances, and to whose beneªt? The hypothesis states that these new models of net-worked activities can lead to development outcomes that are both inclusive and transformative. The theory of open development emerged through observation and experience. The importance of openness for ICT4D came to light following a long day of meetings at a secluded farm near London, Ontario in 2008. Many of the participants had been grappling with the future of ICT4D, and after hav-ing drawn an issue map, participants had an “ah ha ” moment. The issue of “openness ” in IT systems, policy, and development sectors seemed to permeate every element of our (IDRC) ICT4D program-ming. From access to use, and from content to creation, it appeared that some form of openness was a component of much of the research we supported, including open participation in use, open licens-ing to provide services, open content, open source, and open government. Openness is, however, perhaps a better marketing term than analytic concept. Its fuzziness and cur-rent trendiness make it susceptible to multiple interpretations and co-option by actors who subscribe to a range of positions and ideologies. For example, openness is used to describe unfettered markets, but it also describes, for others, the justiªcation of state support for maintaining access to public goods. Others have even seen the underlying “open source ” ethos, which questions principles of ownership, as akin to socialism. In this special issue, we differentiate ourselves from these perspectives. We are concerned with open development; i.e., openness that serves the purpose of development, not openness for openness’ sake. But let’s not get ahead of ourselves; ªrst we must be clear about what openness and open development mean.
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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 | 0.009 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.017 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".