Decoding Financial Inclusion in a Post-War Jurisdiction Sri Lanka: A Case Study
Bibliographic record
Abstract
This qualitative study examines the complex interplay between the financial regulatory landscape and financial inclusion in a post-war jurisdiction. The global debates surrounding the deployment of financial inclusion initiatives virtually center on many legal and non-legal discourses, thereby making this a significant study. This study further identified specific thematic strands which highlight how financial inclusion is regulated and administered in a post-war jurisdiction by amplifying the lived experiences of individuals that are caught between the regulatory structure of financial inclusion. In particular, this doctoral research further examines how stakeholders engaged in financial inclusion have shaped the financial regulatory landscape. By applying a local level analysis of banking practices coupled with daily lived experiences, this research aimed to explore the strengths and limitations in the delivery of financial inclusion efforts. The study employed an interdisciplinary approach, which created narratives contextualized within the jurisdiction this study was conducted. This study seeks to present theoretical and legislative developments that uncover how banking law is interlaced in policy and cultural formation using financial inclusion as an illustrative vehicle. This study is further designed to showcase theoretical and legal influences, as well as a guide in navigating this legal research project by providing original contributions of the fieldwork conducted in a post-war jurisdiction.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".