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<scp>Stacking the Deck: Idling and Reactivation of Capacity in Offshore Drilling</scp>

2008· article· en· W2049347841 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Economics & Management Strategy · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCapital Investment and Risk Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLeaseDrillingDeckSubmarine pipelineDrilling rigOffshore drillingPetroleum engineeringFossil fuelNatural gasBusinessEngineeringWaste managementFinanceMechanical engineeringStructural engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Independent drilling contractors own all offshore drilling rigs, which they lease to oil and gas companies for use in their pursuit of their exploration and development plans. Oil and gas companies' demand for these rigs can vary quickly and dramatically in response to changes in the world market for oil and natural gas. As a result, drilling contractors often try to manage excess capacity by idling rigs (known in the industry as “stacking” a rig), reactivating them when demand recovers. This paper examines these decisions over the course of a price cycle in 1998–2000 to investigate the role of firm and rig heterogeneity in determining drillers' decisions about idling and reactivating capacity.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.083
GPT teacher head0.217
Teacher spread0.134 · 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