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Record W7126749338

Large Hotels Reach a New Statistical Low

2024· article· W7126749338 on OpenAlexaboutno aff
Crocker H. Liu, Adam D. Nowak, Robert (1538?-1574). Compositeur White

Bibliographic record

VenueeCommons (Cornell University) · 2024
Typearticle
Language
FieldBusiness, Management and Accounting
TopicFranchising Strategies and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)DebtDatabase transactionRevenueInterest rateRate of returnFell
DOInot available

Abstract

fetched live from OpenAlex

Only the Midwest, South Atlantic, and West South-Central regions posted moderate single-digit hotel-price gains in the first quarter 2024 (Midwest, 3.2%; South Atlantic, 3.8%; and West South-Central, 1.6%). Hotels in gateway cities experienced a reversal, exhibiting better performance than hotels in non-gateway cities this quarter. Transaction volume fell year over year and quarter over quarter for both large and small hotels in gateway and non-gateway cities. Standardized prices of large hotels continue to soften while those of smaller hotels remain relatively stationary. The cost of hotel debt financing and the delinquency rate for hotels rose in the recent quarter, even though credit spreads continued to tighten and relative risk narrowed. As in prior periods, borrowing costs still exceed the return on hotels. Expect to see a rise in the price of large hotels and a decline in prices for small hotels next quarter based on our leading indicators of hotel price performance.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.064
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0640.016

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 head0.199
Teacher spread0.175 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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