Entrepreneurship and Educational Leadership Development: Canadian and Australian Perspectives.
Bibliographic record
Abstract
ABSTRACT: This article reports the entrepreneurial activities of two university faculties, one Canadian and the other Australian, that were designed to meet the educational needs of students and to garner the resources necessary for program delivery. A conceptual framework for educational entrepreneurship, containing six dimensions, is proposed. The dimensions are: innovative behavior, networking, time-space communication framework, local-global perspective, educational organizations as knowledge centers, and integrated face-to-face and Internet-based learning. Major considerations suggested for entrepreneurial initiatives include access, equity, quality, and sustainability. Educational entrepreneurship is defined as the strategic focus on creating short and long-term opportunities for learning that will make a significant difference for individuals and their societies. Elements of educational entrepreneurship highlighted are strategic planning, the capacity to make responsible but timely decisions, business acumen, faculty development, and strategic alliances. Entrepreneurial leadership must be found among academic and support staff, as well as students. Impact on students is discussed. Other lessons learned include the need for a multi-faced approach to institutional change that incorporates a clearly articulated educational vision, well developed policies and procedures to guide action, sustainable funding plans, and evidence-based practices. Although educational entrepreneurship is reported to be difficult to achieve and seen as vulnerable to changes in personnel and political influences from within the organization and beyond, it is seen as providing a more equitable access to graduate studies and promoting growth in social and human capacity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".