Identification of the Existing Social Problems and Proposing a Sustainable Social Business Model: Bangladesh Perspective
Bibliographic record
Abstract
Social Business, comparatively as emerging concept, deals with social objective and betterment while being financially self-sufficient. The profit-maximizing orientation of traditional business firms often ends up with the exploitation of the under-privileged people of the society. Hence this research attempts to explain the prospect of implementing social business by private organizations to address those social problems which are challenging the lives of the under-privileged people of developing country like Bangladesh. The research is an exploratory qualitative research which uses in-depth interviews and survey method from 60 respondents to identify the existing major social problems and regression analysis to discuss the sustainability of social business in solving such problems. The study also proposes a financially sustainable social business model which actually combines the cause driven motive from a social perspective as well as sustainable orientation from business perspective. Finally the research initiates the necessity of implementing this mandatory drive by all socially responsible private organizations as the scopes of social business in serving the under-privileged section of the developing nation is very optimistic and optimal.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".