The Entrepreneurial Process in a Remote Island Context: The Case of Madeira
Bibliographic record
Abstract
This paper studies the entrepreneurial phenomenon on a remote island to assess the effects of the spatial location on the entrepreneurial process. A qualitative approach was adopted to conduct this research, through a multiple-case study of 8 entrepreneurs from the island of Madeira, an autonomous Portuguese region in the Atlantic. The primary goal of this study is to characterize the entrepreneurial process in remote islands. This study adopts Bygrave’s (2009) definition and model of the entrepreneurial process. The findings show that the geographical environment on remote islands influences most phases of the entrepreneurial process. The identification of business opportunities will vary greatly between sectors of activity. Additionally, island-based entrepreneurs were more motivated by push factors, which suggests that the entrepreneurial landscape in remote islands will be populated by necessity entrepreneurs. Moreover, findings also demonstrate that remote island entrepreneurs are more preoccupied with firm survival than they are with growth. Finally, this study also discusses the impact of advances in information technologies on the entrepreneurial process on small and remote islands.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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 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".