Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the roles of peripherality and centrality in relation to entrepreneurial learning and development. Peripherality has previously been considered from a mainly geographical perspective as being remote, loosely connected and marginal. A broader conception of the topic is addressed, asking: in what ways is peripherality relevant to entrepreneurial learning? How can centre-peripheral connectivity enhance this? What are the implications for communities, learners and educators? Design/methodology/approach Discourses of entrepreneurship development relating to policy, economics, geography and culture favour the concept of centres, which attract attention, resources, activities and people. Whilst peripherality is an enduring topic of interest in regional studies, it is widened through using the conceptualisation of legitimate peripheral participation in social learning as a methodological lens for the study. A case study of the technology sector in Cape Breton, Canada is included to illustrate peripheral entrepreneurship. Findings The paper suggests ways in which peripheral-central relationships can be a positive factor in entrepreneurial learning. It suggests that rebalancing the bidirectional “flow” of knowledge, talent and resources between centres and peripheries can enhance the value of peripheral entrepreneurship, learning and innovation. Social implications The paper connects with prior work on community economic development, offering observations for entrepreneurial learning and development of knowledge-intensive businesses in peripheral areas. Boundary-spanning leadership and skills are required to facilitate peripheral-central interaction and entrepreneurship. Originality/value Peripherality is defined more widely than in prior work, suggesting peripheral learning is part of the fundamental human experience and offers new insights, innovations and opportunities which can create shared value. A conceptual framework for peripheral-central entrepreneurial learning is proposed, which may assist in rebalancing central-peripheral value creation, innovation and regeneration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".