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Record W4288988821 · doi:10.33423/jabe.v24i3.5288

The Long-Run Equilibrium of Industry Population and Bottom Lines: Analysing the Near-Perfect Restaurant Industry

2022· article· en· W4288988821 on OpenAlexvenueno aff
Leiv Opstad, Robin Valenta

Bibliographic record

VenueJournal of Applied Business and Economics · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsBankruptcyProfit (economics)BusinessIndustrial organizationPopulationEconomicsCompetition (biology)Barriers to entryNorwegianProfit marginMonetary economicsMarket economyMicroeconomicsMarket structureFinance

Abstract

fetched live from OpenAlex

The establishment and bankruptcy of businesses is a crucial aspect of the market economy. The market in which restaurants compete is characterized by few barriers to entry, strong competition, low marginal rates of profit, and high levels of bankruptcy. Using publicly available panel data of all Norwegian restaurants, we examine the determinants of market levels of entry and exit. In theory, the driving force in the space of market turnover is the marginal rate of profit in the industry. There is a strong link between the profit rates in the sector and number of firms leaving and entry the marked.

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)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.014
GPT teacher head0.210
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

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

Citations6
Published2022
Admission routes1
Has abstractyes

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