Two Sides Of The Same Coin? A Panel Data Approach To The Innovation-Standard Relationship
Bibliographic record
Abstract
Previous studies have shown an ambivalent relationship between standards and innovation while emphasizing the need to clarify the relationship and uncover their possible causal link. This paper revisits the standard-innovation relationship with the ISO 9001 standard, and patents applications as indicators of standards and innovation, respectively. Using a panel dataset of 81 countries covering the period 1993-2019, we find that ISO 9001 certification is positively associated with innovation. Our fixed-effects and system GMM estimates show that doubling the number of ISO 9001 certificates obtained at the national level increases innovation by 1.3-2.2%. The results vary according to the edition of the standard and the countries’ level of development, whereby developed countries seemed to benefit more from the international quality management standards. The paper also suggests that official development assistance (ODA) may be a vehicle through which wealthier countries can help developing ones harness the benefits of standardization.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".