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Record W3021346374

First Quarter 2020: Gird Your Loins

2020· article· en· W3021346374 on OpenAlexaboutno aff
Crocker H. Liu, Adam Nowak, Robert M. White

Bibliographic record

VenueCornell Peter and Stephanie Nolan School of Hotel Administration (Cornell University) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicConferences and Exhibitions Management
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Computer scienceEnvironmental scienceGeography
DOInot available

Abstract

fetched live from OpenAlex

Hotels in all regions experienced negative price momentum this quarter with hotels in the New England area having the worst price performance. Hotels located in gateway cities were especially hard hit. Hotel financial operating performance based on economic value analysis (EVA) has turned negative, indicating that hotel returns are coming primarily from future price appreciation. The prices of large and small hotels have both trended downwards toward their long run average from the perspective of our moving average trendlines and standardized unexpected price performance metrics. The cost of hotel debt financing has fallen this quarter while the cost of equity financing has increased, making it costlier to borrow equity capital. In terms of risk premiums, the risk premium for hotels has risen compared to the risk-free rate. Besides this, the relative risk premium that lenders require for hotels over and above other commercial real estate has also increased, indicating that lenders are demanding a higher compensation for originating hotel loans. A reading of our tea leaves suggests that both large and small hotels are expected to decline in price. This is report number 34 of the index series.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.234
Teacher spread0.179 · 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 teacher head, not a consensus.

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
Published2020
Admission routes1
Has abstractyes

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