Bibliographic record
Abstract
Many brands are on the wane. Private label dollar share is growing in the United States, from 14.7 % in 1997 to 15.1 % in 2002 (BCG-IRI study), excluding Wal-Mart, where private label share growth is also evident. Price premiums are eroding. Over the past 25 years, consumers have become significantly more price sensitive (Bijmolt, van Heerde and Peters 2005). It is often contended that retail consolidation is to blame; making it more difficult to maintain margins in the face of trade pressure. For example, in the late 1990’s Vlasic started to discount its pickles by selling them in a gallon jar. Wal-Mart became interested and asked Vlasic to price to a $2.99 retail price point and sales at Wal-Mart quickly comprised 30 % of its business. However, the gallon jar cannibalized Vlasic’s business at other retailers and shrank its margins by 25%. When Vlasic asked for relief, Wal-Mart responded by reviewing its commitment to the Vlasic line. By 2001, Vlasic had filed for bankruptcy, in part as a result of shrinking margins. Yet some firms have successfully countermanded this trend. In 2003 Foot Locker, which had quickly grown to be the largest shoe distributor and 10 % of Nike’s sales, cut
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.704 | 0.473 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".