Rural Living Labs: Inclusive Digital Transformation in the Countryside
Bibliographic record
Abstract
Digital transformation (DT) has received increasing attention in recent years. Up until now, most of the current studies focus on digital transformation in advanced and dense societies, especially urban areas and technologies. Hence, the phenomenon of DT is under-researched in the context of rural and sparsely populated contexts. This study aims at exploring how a rural living lab (RLL) can be shaped and how this approach can be designed to support digital transformation processes in rural contexts. In so doing, following a design science research methodology (DSRM) approach, we have made an artefact (that is, RLL framework) that is an "instantiation" that supports user centric digitalization of rural areas. The designed framework is developed based on the key components of "traditional" and "urban" living labs, as well as empirical data which was collected within the context of the DigiBy project. The DigiBy project aims at conducting DT pilots in rural areas to elevate peoples' understanding of digitalization and the application of digitalization opportunities for service development in rural areas in the north of Sweden. As a result of these studies, five key components that guide the design of digital transformation pilots in rural areas emerged, namely: 1) rural context, 2) digitalization, 3) governance, control, and business mode, 4) methods facilitating DT processes, and 5) quintuple helix actors. We also offer an empirically derived definition of the rural living lab concept, followed by avenues for future research.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".