Resilience revisited : assessing the impact of the 2007-2009 recession on 83 canadian regions with closing thoughts on an elusive concept
Bibliographic record
Abstract
Prenant la récession de 2007-2009 comme exemple d’un choc exogène, nous proposons une analyse de la « résilience » de 83 régions canadiennes en utilisant deux indicateurs : le taux de chômage (TC); la croissance de l’emploi (CE). L’analyse nous sert de laboratoire pour un regard critique sur « résilience » comme concept utile en géographie économique. Nos résultats varient en fonction de l’indicateur employé et de l’interprétation donnée à la résilience. Si l’indicateur est CE, 65 régions ont « rebondi » (CE positive après le choc), mais seulement 36 ont retrouvé le rythme de croissance d’avant la récession, et seulement 14 se qualifient comme « résilientes » si nous retenons aussi le critère « résistance » (au choc). Si l’indicateur est TC, 19 régions ont rebondi, les différences attribuables aux réactions variables des travailleurs. Nous concluons que « résilience » demeure un concept difficile à saisir, dont la définition opérationnelle restera problématique. \n=====Abstract Viewing the 2007-2009 recession as an exogenous shock, the paper proposes an assessment of the ‘resilience’ of 83 Canadian regions using two metrics: the unemployment rate (UR); employment growth (EG). The assessment serves a laboratory for a reflection on ‘resilience’ as a useful concept in economic geography. Results vary depending on interpretations of ‘resilience’ \nand metric used. If EG, 65 regions ‘rebounded’ (positive after the shock) but only 36 recovered pre-recession growth paths and only 14 qualify as ‘resilient’ if a ‘resistance’ criterion is added. If UR, 19 regions ‘rebounded’, differences due to varying labour force responses. We conclude that ‘resilience’ is an elusive concept whose operational definition must remain problematic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".