Mobilizing a pluralist theoretical approach to understand microlending digital platforms: the AfricaMC case
Bibliographic record
Abstract
Purpose This study aims to explore how a microlending digital platform connects social investors in developed countries and micro-entrepreneurs in Africa. However, additional research is necessary to discuss how online auction models are designed and implemented and how existing theories can explain their use in the so-called developing countries. Design/methodology/approach The research is based on a single case study: an online auction model for microlending named AfricaMC. Two main methods collected empirical data, namely, online participant observation, i.e. real-time participation in the online auction market and in the forum of discussions, where the authors observed the processes of microlending transactions as registered members; analysis of online documents, by reviewing forum discussions, analyzing reports, blogs, chats and other materials. Findings The results suggest that using sociological and information systems theoretical lenses in a complementary manner could provide greater value than using economics. Originality/value The study makes two main contributions. First, it mobilizes a pluralist theoretical approach based on economic, sociological and information systems perspectives to improve the understanding of microlending digital platforms using online auction models. Second, it uses the understanding produced from data analysis of one particular African case to validate propositions derived from these three theoretical approaches that might be applied to other cases.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".