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Record W4415186428 · doi:10.1016/j.jdeveco.2025.103665

Digital revitalization or useless effort? Public e-commerce support and local specialty sales

2025· article· en· W4415186428 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Development Economics · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsMcGill UniversityGovernment of SaskatchewanConcordia UniversityUniversité Laval
FundersFudan UniversityUniversité Laval
KeywordsSpecialtyKey (lock)Website designThe Internet

Abstract

fetched live from OpenAlex

We examine how a government-initiated e-commerce platform (GEP) affects sales of a local specialty in China’s Pu’er tea market. Using a unique dataset from field experiments and surveys of 983 farmers, we examine changes in online and offline sales over time. We employ two-way fixed effects (TWFE) models to identify the causal impact of GEP access. The results reveal significant substitution effects: access to the GEP increases online sales by 16.649% and decreases offline sales by 15.549%, indicating an overall shift from offline to online sales. On the extensive margin, households that previously sold only offline become more likely to sell online. On the intensive margin, adopters expand their online channels and offer a wider range of tea qualities. The mediation analysis suggests that the increase in online sales channels and product variety accounts for the impact of GEP access on the shift to online transactions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.220
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it