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Record W3173807302 · doi:10.24908/pceea.vi0.14969

EFFECT OF MENTORSHIP ON THE EARLY ENTREPRENEURIAL JOURNEY OF UNIVERSITY STUDENTS

2021· article· en· W3173807302 on OpenAlexafffundvenue
Loujein Mouammer, Carlos Bazán

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2021
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsMemorial University of Newfoundland
FundersAtlantic Canada Opportunities Agency
KeywordsMentorshipGraduation (instrument)EntrepreneurshipCredibilityThematic analysisMedical educationValue (mathematics)PsychologyPerceptionPedagogyManagementSociologyQualitative researchMedicinePolitical scienceEngineeringSocial scienceComputer science

Abstract

fetched live from OpenAlex

Acknowledging the value of entrepreneurs in today’s society, universities are looking into mentorship to improve their support system for students considering entrepreneurship as a viable career path after graduation. This paper reports the main findings of a systematic literaturereview aimed at understanding the role that mentorship plays during the early entrepreneurial journey of university students. That is, identifying what motivates students to seek mentorship and recognizing the critical elements of successful mentorship programs that develop robustmentor-mentee relationships. The systematic literature review classified the selected articles into three thematic categories: mentoring in entrepreneurship, gender differences in mentoring, and mentorship programs in business incubation. Findings in the combined categories suggest that a positive mentoring experience depends on the mentor’s credibility and connection inthe business world and the mentee’s perception of similarities between their mentor and themselves.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.009
GPT teacher head0.250
Teacher spread0.240 · 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 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

Citations9
Published2021
Admission routes3
Has abstractyes

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