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Record W4362721281 · doi:10.14738/abr.114.14396

Internal Governance Mechanisms and Performance of Microfinance Institutions in Togo

2023· article· en· W4362721281 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueArchives of Business Research · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsMicrofinanceCorporate governanceBusinessContext (archaeology)BoomSustainabilityAccountingFinancial systemEconomic growthEconomicsFinanceGeographyEngineering

Abstract

fetched live from OpenAlex

Despite the boom in microfinance in Togo, the sector is seriously shaken by serious crises that threaten its performance and cast doubt on its sustainability. To explain performance crises to which microfinance institutions are subject, governance is regularly mentioned. This paper aims to identify internal governance mechanisms that can influence microfinance institutions’ performance in Togolese context. It is found out at the end of this paper that board of directors (the board size, presence of women on the board, duration of directors’ term of office and frequency of board meetings) influences financial and social performance of MFIs. On the contrary, the fact that MFI belong to a network or not, and its legal status have no effect on its performance.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.150

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.287
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it