Cameroonian perspectives on entrepreneurship: discovering subcultural heterogeneity
Bibliographic record
Abstract
Purpose This paper aims to explore cultural attitudes and beliefs about entrepreneurship in the southwestern region of Cameroon. This study also identifies the existence of subcultural variations with important implications for the development of entrepreneurial activities in Cameroon. Design/methodology/approach The paper uses the hybrid qualitative/quantitative Q methodology to survey and analyze a purposively diverse sample of individuals and thereby discover subcultural structures and patterns to the attitudes and beliefs that exist in Cameroonian culture. Findings This study discovers three distinct subcultures that differ significantly in their attitudes and beliefs about entrepreneurship. These subcultures can neither be predicted from commonly used national measures of cultures, such as those of Hofstede, nor are they directly attributable to regional effects. Research limitations/implications The author calls into question the continuing use of national culture as a construct in explaining and predicting entrepreneurial activities, through discovery of subcultures at odds with national measures. Further research should be undertaken to assess the prevalence within Cameroonian society of the three widely different subcultures identified here. Practical implications This paper highlights the importance of incorporating subcultural variations in attitudes and beliefs (whether regional, tribal or other) in the development and implementation of public policies to affect national entrepreneurship. Originality/value The paper applies a novel methodology to qualitatively explore the subjective variations in the meaning and value of entrepreneurship in Cameroonian society, and to quantitatively develop a structure or typology to these variations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".