MétaCan
Menu
Back to cohort
Record W1966077602 · doi:10.1080/13657305.2011.549408

BUYING POWER IN UK RETAIL CHAINS: A RESIDUAL SUPPLY APPROACH

2011· article· en· W1966077602 on OpenAlexaff
Frank Asche, Linda Nøstbakken, Atle Øglend, Sigbjørn Tveterås

Bibliographic record

VenueAquaculture Economics & Management · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSupply chainResidualMarket powerExploitIndustrial organizationLerner indexIndex (typography)EconomicsPower (physics)MicroeconomicsBusinessMarketingComputer science

Abstract

fetched live from OpenAlex

The growth of large supermarket chains has raised concerns that these companies can exploit oligopsony power. In this article, we specify a residual supply schedule to investigate the degree of oligopsony power in seafood retailing. Based on the residual supply elasticity, one can also derive a Lerner-type index to measure the degree of market power. Our empirical analysis of the largest supermarket chains in the United Kingdom provide no evidence of oligopsony power for three key seafood products, cod, salmon and shrimp.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.001

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.

Opus teacher head0.033
GPT teacher head0.181
Teacher spread0.148 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueAquaculture Economics & ManagementSame topicEconomics of Agriculture and Food MarketsFrench-language works237,207