Technology platforms as an ICT4D model for business development
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.
Bibliographic record
Abstract
Platform technologies provide cost-effective models of exchange, use a huge amount of data to suggest different products for customers and create a scalable space for the unprivileged and underserved entities to do business online. Yet the unlimited opportunities created by platform technologies can collapse into different forms of institutional voids and socio-economic inequalities. This editorial discusses the unique benefits of platform technology and ICTs for business development and explore emergent knowledge of consumers as an opportunity to shape the design, implementation, use and evaluation of platform-based business models that can address institutional voids and be trusted for development. Taking inspiration from emergent knowledge and articles published on the potential of platform technology and ICT infrastructures for development in this Special Section, we advance Ciborra’s original conceptualization of platform as a unique organizing technology to innovate organizations by arguing that platform-based business models can be positively leveraged to mitigate institutional voids in marginalized communities. This offers an insightful contribution for researchers, practitioners and policymakers to empower consumer participation in the design of platform-based business models to maximize the full and equitable potential of technology platforms and ICTs for business and socio-economic development.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it