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Record W2592901385

Major Research Project

2016· other· en· W2592901385 on OpenAlexaboutno aff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2016
Typeother
Languageen
FieldSocial Sciences
TopicFeminist Theory and Gender Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipNegotiationStakeholderProcess (computing)Public relationsField (mathematics)Social entrepreneurshipSociologyManagement sciencePolitical scienceEngineeringComputer scienceSocial science
DOInot available

Abstract

fetched live from OpenAlex

In an exploration of Women’s Entrepreneurship in Canada, this project seeks to re-examine the commonplace of the male as the prime entrepreneurial role model while uncovering the experience and potential of women entrepreneurs for the expansion of economic growth and social impact. My research demonstrates that women entrepreneurs not only have the potential to negotiate between two complex entrepreneurial systems to reveal a middle ground, but very likely have been leaders in developing a vision of Canadian society wherein businesses do not act in conflict with the good of the people, but rather, in concert with it. I derived this knowledge by adapting a qualitative and design research method known as the Double Diamond design model (Design Council, 2005). This method emphasizes empathetic ‘problem finding,’ rather than comparisons with men in the field, to uncover a broad range of issues surrounding women’s entrepreneurship. As a design method, Double Diamond includes an iterative ‘problem solving’ process that delivers ideas for interventions to improve women entrepreneurs’ experience and impact. \nMy literature review unwraps the dichotomy of approaches held by researchers to studying and measuring women entrepreneurs’ impact on the Canadian economy and society. \nIn Methodology, I describe my research approach, framed by the Double Diamond’s four distinct phases: Discover, Define, Develop and Deliver. I incorporate additional design methods in each phase—expert interviews, journey mapping, stakeholder mapping, affinity diagramming and sequence modeling—to organize, understand, and suggest the \nclearest ways to communicate what I learn. This leads to the observations and insights found in Findings, where a synthesis of takeaways is followed by design-derived recommendations for advancement women’s entrepreneurship and the study thereof. The project concludes with a reflection on the inquiry process and implications of the study for general entrepreneurship literature and the overall value for aspiring women entrepreneurs.

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.703
Threshold uncertainty score0.995

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0100.002
Scholarly communication0.0070.003
Open science0.0040.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2970.118

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 head0.188
GPT teacher head0.436
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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