The Ottawa Group’s Contributions to Consumer Price Index Methodology: Institutional Contexts, Epistemic Shifts, and Quality Adjustment Debates (1994-2024)
Bibliographic record
Abstract
The statistical treatment of quality change in Consumer Price Indices (CPIs) has long posed conceptual and operational challenges for national statistical offices. Beyond formal harmonization efforts led by international organizations, the creation of the Ottawa Group in 1994 established an informal expert forum in which statisticians and economists could confront these challenges through a mixture of practical experimentation and theoretical discussion. This article reconstructs the institutional and political conditions that enabled the emergence of the Ottawa Group and examines how this space contributed to the evolution of CPI methodology, particularly the question of quality adjustment, over the period 1994–2024. Drawing on an original database of 488 contributions from the Ottawa Group, we combine qualitative historical reconstruction with bibliometric, co-citation, and thematic analyses to map the epistemic configurations that structured the Ottawa Group debates. The results reveal the coexistence of two enduring methodological orientations, one grounded in index-number theory and the other in pragmatic statistical practice, alongside a progressive consolidation of collaborative networks within the Group. Taken together, these findings show how the Ottawa Group served as both a laboratory for methodological innovation and a site where divergent conceptions of “quality” were negotiated, contributing to the broader history of quantification and international statistical harmonization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.014 | 0.025 |
| Science and technology studies | 0.017 | 0.024 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".