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Record W7112255868

Leadership Strategies Indigenous Canadian Entrepreneurs Use to Sustain Their Business

2024· article· W7112255868 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks (Walden University) · 2024
Typearticle
Language
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousSmall businessGovernment (linguistics)Thematic analysisEntrepreneurshipPromotion (chess)Face (sociological concept)RevenueQualitative research
DOInot available

Abstract

fetched live from OpenAlex

Indigenous Canadian small business entrepreneurs face a high risk of failure within five years of operation. These entrepreneurs encounter challenges such as limited access to capital and skilled employees and must develop strategies to sustain and grow their businesses. Grounded in the theory of constraints, the purpose of this qualitative multiple-case study was to explore strategies employed by Indigenous small business entrepreneurs to effectively sustain their businesses beyond 5 years. The participants were six Indigenous small business entrepreneurs in British Columbia who implemented strategies to sustain their businesses beyond 5 years. Data were collected through semistructured interviews and by reviewing income statements, job postings, strategic plans, business models, and marketing and promotion strategies provided by the entrepreneurs. Through thematic analysis, eight themes emerged: (a) managing people, (b) wielding market and government influence, (c) financing and the cost of goods and services, (d) building relationships with people and community, (e) understanding the business and market, (f) utilizing tools and metrics, (g) building capacity and mentorship, and (h) managing cashflow and diversifying revenue streams. A key recommendation is for Indigenous entrepreneurs to hire leaders with cultural competency, as well as a strong understanding of financial constraints. The implications for positive social change include the potential to implement effective sustainability strategies that increase employment, improve opportunities for Indigenous employees, and strengthen the local workforce, ultimately leading to greater employment and retention.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.029
GPT teacher head0.189
Teacher spread0.160 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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