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Record W3125823606 · doi:10.64628/aa.nfvheyed9

The rise and rise of Aldi: two decades that changed supermarket shopping in Australia

2021· article· en· W3125823606 on OpenAlexaboutno aff
Gary Mortimer, L Grimmer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)AdvertisingBusinessMainstreamGermanLoyaltyMarketingGeographyPolitical science

Abstract

fetched live from OpenAlex

Twenty years ago, on January 25 2001, a virtually unknown German supermarket chain quietly opened its first stores in Australia. The two stores – one in Sydney’s inner-west suburb of Marrickville, the other in the outer south-west, near Bankstown Airport – were small, about a quarter the size of a mainstream supermarket. Each stocked just 900 products, 90% of which were unknown brands. Shoppers had to bring and pack their own bags themselves. To use a trolley required a “gold coin”. They didn’t seek to entice customers with “loyalty” rewards or other gimmicks. Few Australian supermarket executives at the time would have considered them models for success. They couldn’t imagine the impact Aldi would have on Australia’s retail sector and shopping habits.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.219
Threshold uncertainty score0.436

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.004
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.078
GPT teacher head0.351
Teacher spread0.273 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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