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Record W2022056600 · doi:10.2304/csee.2002.5.1.29

Instilling the Spirit - Learning Strategies for the New Millennium: The Bachelor of Education in Enterprise Education Program

2002· article· en· W2022056600 on OpenAlexaff
Eugene Luczkiw

Bibliographic record

VenueCitizenship Social and Economics Education · 2002
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsBrock University
Fundersnot available
KeywordsFacilitatorGeneral partnershipCurriculumEntrepreneurshipSociologyContext (archaeology)BachelorEngineering ethicsKnowledge managementPublic relationsPedagogyEngineeringPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The mental models, learning styles and world views that people internalized in last century's industrial era no longer serve the demographic, economic, environmental, and social needs of the 21st Century. New learning methodologies and strategies are needed to connect each individual's distinct essence of being with emerging opportunities in today's highly disruptive environment The Institute for Enterprise Education (IEE) has developed such a curriculum that seeks to connect the learner and facilitator with learning opportunities that enhance their capability and connection with emerging opportunities in the external environment This paper. provides a global context for the need to instill the entrepreneurial spirit into every subject field of the educational spectrum; evaluates entrepreneurship as an effective process for interacting with today's highly disruptive global environment; identifies scientific paradigms that provide a systems approach to understand the new rules and the nature of interaction (Science of Complexity); synthesizes the theory behind complexity sciences and the practice of entrepreneurship to provide a learning strategy for each individual (Human Factor); develops an evolutionary path for the Bachelor of Education in Enterprise Education program for new student teachers, a symbiotic partnership between IEE and Brock University's Faculty of Education.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.162
GPT teacher head0.394
Teacher spread0.232 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations2
Published2002
Admission routes1
Has abstractyes

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