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Record W2081687870 · doi:10.1057/palgrave.jors.2601773

A free coordination hull approach to efficiency measurement

2004· article· en· W2081687870 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 the Operational Research Society · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsYork University
Fundersnot available
KeywordsHullData envelopment analysisBinary numberComponent (thermodynamics)Computer scienceZero (linguistics)Mathematical optimizationSample (material)AnalogySimple (philosophy)Set (abstract data type)Operations researchMathematicsEngineeringArithmetic

Abstract

fetched live from OpenAlex

Abstract Superficially, the free disposal hull production possibility set (pps) can be regarded as a binary version of the Banker, Charnes and Cooper pps, in which only one component of the vector, λ, is non-zero and of necessity equal to 1. We therefore propose, by analogy with a pps due originally to Koopmans, a new pps which retains the binary characteristic of the components of λ but permits more than one component to be non-zero. Thus, a given DMU's performance is assessed not only against the individual DMUs included in the sample but also against composite DMUs obtained by simple aggregation. This approach is demonstrated and investigated on a published data set.

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)0.048
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0480.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0030.000
Research integrity0.0000.001
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 head0.274
GPT teacher head0.454
Teacher spread0.180 · 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