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Record W4416382985 · doi:10.1177/0308518x251391204

An empirically grounded conceptual framework of the determinants of economic resilience: Insights from seven major Canadian regions

2025· article· en· W4416382985 on OpenAlexafffundabout
Jesse Sutton, Godwin Arku

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional resilience and development
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsConceptual frameworkConceptual modelResilience (materials science)Set (abstract data type)The Conceptual FrameworkPsychological resilience

Abstract

fetched live from OpenAlex

Investigating the determinants of resilience has been a core research agenda in the regional economic resilience literature. However, no comprehensive conceptual framework of the determinants of resilience currently exists. Instead, the determinants are typically presented as a set or list of factors that influence the economic resilience of regions. A more comprehensive conceptual framework, illustrating how such determinants interact, is therefore needed. To address this gap, this paper develops an empirically grounded conceptual framework of the determinants of regional economic resilience. To do so, this paper conducted in-depth interviews with economic development practitioners ( n = 41) from seven major Canadian regions. In the developed conceptual framework, the paper highlights the interactive nature of the determinants of resilience, the importance of recognizing the ecological limits of regions, and the roles that firm-based and system-based actors play in shaping regional economic resilience.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.785

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0130.009
Scholarly communication0.0050.002
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2025
Admission routes3
Has abstractyes

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