Bibliographic record
Abstract
Recent phenomenal growth in popularity of large warehouse/discount stores has important implications for price measurement. Consumer substitution to such outlets could produce a bias in consumer price indexes (CPIs), which may be exacerbated by unrepresentative sampling and discount outlets’ apparent slower rates of price increases. It is shown that in 1990‐96 unit value indexes rose at a lower rate than the corresponding Canadian CPI subaggregate indexes for other household equipment, non‐prescribed medicines, and audio equipment, and biases arising from unrepresentative sampling and differential rates of price increases across outlets have resulted in an additional overstatement for these subaggregates. La croissance dans la popularité des magasins/entrepôts à forts escomptes au cours des der;chnières années a été fort importante et a eu des effets importants sur la mesure des prix. Le comportement du consommateur qui choisit ces magasins pourrait entraîner un biais dans la mesure des indices de prix à la consommation. Un échantillonage non représentatif et le fait que ces magasins semblent avoir des augmentations de prix plus faibles dans le temps peuvent biaiser encore plus les indices. Cette recherche montre que entre 1990 et 1996 les indices de la valeur unitaire ont cru à un taux plus faible que les indices correspondant de prix à la consommation pour des sous‐agrégats comme autre ´equipement des ménages, médicaments non‐prescrit, et ´equipement audio. Il semble que les biais engendrés par les différentiels de croissance des prix entre magasins et un échantillonnage non représentatif se soient traduits par un biais à la hausse dans ces sous‐agrégats
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".