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Record W4410543054 · doi:10.1177/25151274251340711

Taking Entrepreneuring Seriously in Entrepreneurship Education—Conceptual Dimensions and Implications for the Classroom

2025· article· en· W4410543054 on OpenAlexaff
Debora Sara Anspach

Bibliographic record

VenueEntrepreneurship Education and Pedagogy · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsEntrepreneurshipEntrepreneurship educationSociologyPsychologyMathematics educationPedagogyPolitical science

Abstract

fetched live from OpenAlex

The scholarly and educational field of entrepreneurship has rapidly expanded and evolved over time, carrying promises of enhanced economic growth and prosperity for nations that harness it. Such speedy establishment and expansion of entrepreneurship education, however, may have obscured the onto-epistemological underpinnings of our pedagogical methods and students’ learning. Thus, the following questions may need attention: Why does entrepreneurship education need to be refocused? Under what onto-epistemological rationale should such renewal be brought forward? And what could be gained for the field of entrepreneurship education? This conceptual paper opens discussions about these three questions from the perspective of entrepreneuring. Entrepreneuring with its underlying process and practice onto-epistemology may be a propitious “conceptual attractor” for the classroom, bringing forward four key pillars for entrepreneurship education to be taken into account: (1) situatedness in space and time; (2) relatedness and open-endedness; (3) everyday creativity and play; (4) reflexivity. The paper contributes to entrepreneurship education by proposing specific learning objectives, teaching methods, and assessment practices for each of the aforementioned four pillars and invites educators to consider entrepreneuring, social and more mainstream perspectives of entrepreneurship not as exclusive but as integrative perspectives that can be unified under the “socializing” umbrella of entrepreneuring.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.326
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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