Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Subject area The case is suitable for undergraduate and MBA courses: strategic management, social entrepreneurship. Study level/applicability Masters, Bachelors. Case overview In Fortaleza, January 2008, an urban microfinance manager and the planning committee of Crediamigo, Brazil's largest microfinance institution need to devise an entry strategy to Rio de Janeiro's microfinance market. A part of the Banco do Nordeste, and a regional development bank for ten years, Crediamigo has 400,000 clients in the Northeast of Brazil. Its objective is to double its clients base for 2011; Rio de Janeiro's market was the next priority. Crediamigo has two options. The first consists of partnering with VivaCred, a small experienced microcredit non-governmental organization (NGO) which operates in Rio de Janeiro's slums. VivaCred was a microfinance NGO with relatively low organizational capabilities and with a low performance in terms of loan repayment. Its lending methodologies were different from Crediamigo's experience. The second option was to set up a new branch of Crediamigo in Rio and to shape it in Crediamigo's image. The committee was aware that this, “far away from home”, would be a costly and slow venture. Expected learning outcomes After using this case, students will: have been exposed to the strategic, managerial and operational challenges of microfinance expansion in an emerging country; understand better the market entry strategy (acquisition/integration of an organization vs green field) in such a context; have discussed the conditions related to the replication of microcredit methodologies (individual, group and village lending methodologies) in their contexts of operations. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it