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Record W2902237166 · doi:10.11648/j.ajmse.20180305.15

Career Functions Performed by Mentors of Millennial Generation Entrepreneurs

2018· article· en· W2902237166 on OpenAlexaffabout
Nathanael David Robert Moulson

Bibliographic record

VenueAmerican Journal of Management Science and Engineering · 2018
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsGeneration xWork (physics)Career pathGeneration yPublic relationsFunction (biology)Set (abstract data type)New VenturesCareer developmentPopulationMarketingBusinessPsychologyManagementEntrepreneurshipSociologyPolitical scienceBusiness administrationEngineeringFinanceSocial psychologyDemographic economicsEconomics

Abstract

fetched live from OpenAlex

Millennial generation entrepreneurs are showing a higher than average interest in starting new companies. This generation is key to economic success in Canada since the millennial generation comprises roughly 25% of the Canadian population. Mentors may make the difference between success and failure of these new ventures. This multiple case study explored 6 millennial generation small business owners participating in the Futurpreneur Canada mentoring program. Data included semistructured interviews with participants of the Futurpreneur mentoring program, experience profiles of these participants, and public information about the Futurpreneur program. The analysis of the data demonstrated that mentors provided career support by serving in the following roles: (a) advisor for entering new markets, (b) connector to experts, and (c) advisor on a business function. Insights from this study may help program designers, entrepreneurs, and mentors work together to enable entrepreneurs to develop their organizations and set them on the path to success.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.752
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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