The Use of Social Media in Burkina Faso SMEs: a Tool to Increase Performance?
Bibliographic record
Abstract
L'adoption des médias sociaux par les entreprises du monde entier a augmenté au fil des ans, car l’utilisation de ceux-ci offrent des possibilités de mieux s’implanter sur les marchés visés et de mieux réussir sa stratégie de marketing. Cependant, on sait peu de choses sur la manière dont les petites entreprises en Afrique occidentale utilisent les médias sociaux pour soutenir leurs opérations quotidiennes et améliorer leurs performances. Avec une étude de cas multiples, cet article vise à présenter comment les petites et moyennes entreprises (PME) du Burkina Faso perçoivent les médias sociaux, comment elles les utilisent pour soutenir leurs activités quotidiennes et quels sont les avantages qu'elles en retirent. Un autre objectif de cette étude est d'examiner les plateformes de médias sociaux utilisées par ces PME et les obstacles qu'elles rencontrent lorsqu'elles souhaitent les utiliser efficacement. Enfin, l'impact des médias sociaux sur la performance des PME est aussi présenté.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".