Modeling country image effects through an international crisis
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.
Bibliographic record
Abstract
Purpose The purpose of this paper is to propose and test a longitudinal country‐people image effect model involving a significant negative international incident between countries; study how such a model changes over time; and study the extent of image recovery in terms of how the offending country, people, and its products are perceived. Design/methodology/approach Australian consumers were surveyed before, during, and a decade after the French nuclear testing in the Pacific in 1995. Model testing was conducted using confirmatory factor analysis (CFA) and structural equation modeling (SEM) techniques. Findings The model was strongly supported in all three‐time points. During the crisis, negative feelings toward France/French rose and consumers' response to French products dropped. Country‐people competency has risen over country‐people character in explaining product evaluations. In the final period, the Australian views on country‐people character and product response had more than recovered. The country‐people character beliefs now play a significant role in influencing product evaluations after the crisis than before, while the impacts of country‐people competency on product evaluation and response have diminished dramatically. Product evaluation is fairly stable over time. Originality/value Studies to date have focused on country image at a point in time in relatively stable environmental conditions. The proposed model is helpful in understanding the processes of country‐product image effects through the study of all attitude components and through differentiation of beliefs about country and people production‐related and non‐production related characteristics. The cross‐temporal validation of the model indicates its usefulness for general applicability in country image effects research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it