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Record W6898939202 · doi:10.58067/s64m-x346

Flourish and Grow

2024· article· en· W6898939202 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueConestoga College Repository · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicCrafts, Textile, and Design
Canadian institutionsWestern University
Fundersnot available
KeywordsIndigenousClothingGovernment (linguistics)Promotion (chess)RevenueWork (physics)

Abstract

fetched live from OpenAlex

Flourish and Grow (F&G) was a sole proprietorship based out of London, Ontario, retailing handmade fine art, jewelry, and apparel that conveyed a narrative of the founder’s Indigenous Mi’kmaq culture and values. During the COVID-19 pandemic, Mikaila Stevens, founder of F&G, had ample time to spend at home and developed a newfound passion for beading and creating art as a way to connect with her Indigenous Mi’kmaq culture and values. In the next year, she created a collection of fine art products to expand her business. After obtaining government grants, Stevens was able to expand F&G and forge connections with her customers through her expression and personal creations. Stevens sought to explore her Mi’kmaq ancestry and had a strong desire to create unique introspective pieces that showcased techniques from her heritage. Reflecting on the next steps for F&G, Stevens recognized the urgent need to optimize the product, pricing, promotion and distribution of her sole proprietorship to remain competitive and increase revenue to sustain full-time F&G employment and continue her work of passion. Where should she start?

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.643
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.205
Teacher spread0.188 · 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