Gender and international entry mode
Bibliographic record
Abstract
This article examines whether male- and female-led small and medium-sized enterprises (SMEs) adopt different strategic directions when internationalising. We build on the notion of gendered socialisation and the resource-based view examining gender differences in international entry modes. We also analyse several contingencies in the relationship between gender and internationalisation. Findings indicate that female-led SMEs are more likely to internationalise via export than foreign direct investment (FDI). The results challenge conventional wisdom on the role of resources and capabilities accumulated with manager age in the process of internationalisation; younger female chief executive officers are more likely to internationalise via FDI. The results offer novel insights to the literature on internationalisation of SMEs calling for more attention towards the interplay of social norms and gendered structural arrangements, on the one hand, and entrepreneurial agency, on the other, for a better understanding of the internationalisation of female-led SMEs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".