Social Capital and ICT Intervention: A Holistic Model of Value
Bibliographic record
Abstract
Background: Despite increasing popularity of Social capital, the relationship between social capital and ICT often appears to be an ambivalent one. Existing information systems (IS) literature presented various frameworks and theoretical foundations to facilitate the study of this concept, yet several contradictory findings have been reported indicating a significant knowledge gap in this domain. Current research adopts a holistic approach to address this knowledge gap by answering “How does social capital generate value or benefits in an ICT intervention?” Method: Current research employs a systematic literature review coupled with a grounded theory method to investigate proposed research questions. Results: Primary contributions of the current research include (1) the identification of contextual relationship between contextual factors and social capital dimensions, and (2) development of a holistic model of social capital driven benefits during ICT intervention where the ‘enablers’ and the ‘drivers’ of benefit have been identified. Conclusions: Identification of distinct roles and value-drivers related to social capital will help IS researchers in explaining “how and why” benefits are achieved while employing a social capital lens. Availible at: https://aisel.aisnet.org/pajais/vol11/iss4/3/
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".