MétaCan
Menu
Back to cohort
Record W4213283745 · doi:10.1080/00472778.2021.2017443

Understanding micro-level resilience enactment of everyday entrepreneurs under threat

2022· article· en· W4213283745 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.

Bibliographic record

VenueJournal of Small Business Management · 2022
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsSimon Fraser UniversityUniversity of Victoria
Fundersnot available
KeywordsMindsetIdentity (music)Construct (python library)EntrepreneurshipPsychological resiliencePerceptionSocial psychologyPsychologyAffordanceResilience (materials science)MarketingPublic relationsSociologyBusinessPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

Differences in independent retail small business entrepreneurs’ COVID-19 resilience enactment are investigated using a qualitative retroductive analytic approach. We observed that some entrepreneurs, even in the same industry, sector and city, with similar offerings, chose to adopt online store technologies while others did not. Identity motives are uncovered as a likely explanatory construct, as those with externally focused identity motives generally adopted these technologies while those with internally focused identity motives generally did not. Identity motives appear to influence entrepreneurs’ perceptions of technology affordances, potentially moderating the impact of these perceptions on technology adoption decisions. Contrary to conceptualizations of individual resilience being a trait or process, we find support that resilience is more appropriately viewed as a mindset. Implications for entrepreneurship theory, practice, and education are discussed.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.234
GPT teacher head0.363
Teacher spread0.129 · 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