1\section{Data: snapshot, cleaning, provenance and representativeness}\label{sec:data}23\subsection{Snapshot and samples}4The research copy is a read-only backup of the Fabri-Ka production database taken on 1 November 2026 at 17:38 UTC (application commit \texttt{689c7bb}); the only tables containing personal data (two user accounts, one self-registration) and the derived full-text index were dropped on the production node before the copy left it. The copy holds 465{,}388 product rows, of which 390{,}108 are active and published by the platform's own rules --- gift cards, workshops, subscriptions, tickets and price-out-of-bounds quarantines are excluded upstream --- in 1{,}569 enabled stores, plus 577{,}773 synchronisation events. Table~\ref{tab:sample_flow} and Figure~\ref{fig:attrition} trace the path to the two analysis samples. We drop one store flagged out of mission by the platform, keep one representative listing per (store, normalised title) because many merchants publish colour or format variants as separate products (19{,}245 non-representative listings), and remove eleven \emph{mirror domains} --- language or top-level-domain twins of the same business, detected by domain stem or by a title overlap of at least 90\% of the smaller catalogue --- which would double-count assortments and manufacture within-firm ``cross-merchant'' price pairs. The \textbf{assortment sample} has 370{,}054 listings in 1{,}557 stores and twenty categories. The \textbf{price sample} further requires a Canadian-dollar store and listing, a positive posted price not ``on request'' and at most 50{,}000~CAD (9{,}635 listings have no posted price, 729 are in foreign currency, 78 exceed the cap): 359{,}612 listings. Within the assortment sample, 13.1\% of listings are marked sold out by the merchant, 8.7\% carry a strike-through price, 27.8\% have several variants, 76.7\% carry a merchant SKU and 75.6\% a brand field.56\input{tables/sample_flow}78\subsection{Merchant geography}\label{sec:data_geo}9The platform assigns a region from the discovery source (regional directories), from region mentions on the site, or from a map of forward sortation areas (FSA, the first three characters of the postal code); coordinates are FSA centroids obtained from a public geocoder, never civic addresses. At the snapshot 346 of the 1{,}569 live stores had no region, including the four largest catalogues (a book retailer, a souvenir printer, a trailer-parts seller and a pet-supply retailer). We recovered regions from official geography: for urban FSAs the sector label is matched to the MRNF municipality table (393 stores, 95.9\% agreement with the point-in-polygon of the centroid where both exist), then the platform's own label is kept (865 stores), then the FSA centroid is located in the MRNF administrative-region polygons (82 stores). The order was amended after preregistration (A-001): a first attempt with the Statistics Canada 2021 economic-region layer produced 229 apparent conflicts between platform labels and polygons, of which 99 were a spelling artefact and most of the rest the Brome-Missisquoi/Haute-Yamaska transfer from Montérégie to Estrie that the 2021 layer predates; with the current MRNF layer the platform label and the centroid agree for 89.1\% of stores, and the remaining disagreements (30 after the final rule) are rural FSAs whose centroids fall near a border, which is why the platform label is preferred to the centroid. After recovery, 229 stores (71{,}692 listings, 19\% of the assortment sample) remain without a location; they come mainly from gift directories and search sweeps, are reported as a separate ``Inconnue'' row in descriptive tables, and are excluded from all regional inference. One further caveat: the telephone field of 250 stores is the switchboard of the certification directory that listed them (212 carry the number of Les Produits du Québec); telephones are therefore never used for geography. Table~\ref{tab:region_summary} summarises the regional sample.1011\input{tables/region_summary}1213\subsection{Category labels: audit and classifier (Amendment A-002)}\label{sec:data_categories}14The platform assigns one of twenty categories by keyword rules on the merchant's product type, tags, title and option names. We audited these labels on a stratified random sample of 500 listings (25 per category) annotated independently by two large language models (claude-opus-5-5 and gpt-5.5) given the platform's own taxonomy definitions; the two annotators agree with each other on 94.8\% of listings but with the rule label on only 45.2\% and 44.6\% respectively, so the precision of the rule label against annotator consensus is 0.46 (Table~\ref{tab:cat_audit}). Errors are structured: the ``other'' bin is almost entirely resolvable into industrial, art or home goods; ``art'' absorbs industrial and craft supplies; beverages, alcohol, pets and outdoor goods are frequently mislabelled fashion or art when a merchant's tags are generic. Jewellery, garden and fashion are the most reliable rule labels.1516%%CLASSIFIER%%1718\subsection{Cross-merchant matching: candidates and validation}\label{sec:data_matching}19Tier-A (shared SKU) and tier-B (same brand, identical title) candidates number 1{,}837 and 457 pairs in different stores, of which 1{,}683 and 381 have a comparable variant structure; fuzzy tier C adds 446 (324 comparable) and identical-title-only tier D 2{,}713. On a validation sample of 60 pairs per tier, two independent annotators agree on 87.5\% of pairs; among consensus pairs the share judged the same product is 0.92 for tier A, 0.90 for tier B, 0.77 for tier C and 0.17 for tier D (Table~\ref{tab:match_val}); restricted to comparable-variant pairs, tiers A and B reach 0.90 and 0.96. These are the precision figures we carry into the hedonic analysis; the tier-D figure confirms that identical titles across artisanal shops (``savon à la lavande'') are not the same product.2021\input{tables/match_validation}2223\subsection{External data}\label{sec:data_external}24Regional covariates and geography were downloaded from their official sources with a manifest of URLs, licences, vintages and checksums (Appendix~\ref{app:source}): ISQ population at 1 July 2025, ISQ business locations with employees in December 2025 (all industries, retail NAICS 44--45, manufacturing 31--33), ISQ disposable income per capita 2024 and regional GDP 2024, Statistics Canada Census 2021 land area and density, the MRNF administrative-region and municipality layers (version 2026-10) and the Statistics Canada 2021 FSA boundaries. No recent regional (as opposed to provincial) measure of household or business e-commerce adoption exists; the only regional split of household internet access is the 2012 ISQ survey, which we do not use.2526\subsection{Representativeness}\label{sec:data_repr}27Fabri-Ka's store counts track the regional business base closely in levels --- Spearman correlations with ISQ business locations of 0.91 (all), 0.89 (retail) and 0.93 (manufacturing), and 0.84 with population --- but coverage per thousand business locations varies six-fold across regions (1.8 to 11.1, coefficient of variation 0.43; Table~\ref{tab:external}), with the agri-food and craft regions covered by dedicated directories (Saguenay--Lac-Saint-Jean, Bas-Saint-Laurent, Gaspésie) over-represented relative to Montréal and Laval. This is a discovery artefact, not a feature of the regional economies, and it is the main threat to every regional comparison below; Section~\ref{sec:robust} re-estimates the results on stores discovered through certification and association sources only and without Montréal.2829\input{tables/external_coverage}30