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Record W2221149312

Rationalising Inefficiency: A Study of Canadian Bank Branches

2006· preprint· en· W2221149312 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRePEc: Research Papers in Economics · 2006
Typepreprint
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsnot available
Fundersnot available
KeywordsInefficiencyRationalityIgnoranceEconomicsBounded rationalityIncentiveMicroeconomicsData envelopment analysisSet (abstract data type)Outcome (game theory)Resource (disambiguation)Computer sciencePolitical scienceMathematics
DOInot available

Abstract

fetched live from OpenAlex

Many studies have attempted to explain estimated inefficiency, for instance by bounded rationality, ignorance, lack of incentives or motivation etc. However, the presence of inefficiency remains in conflict with the neo-classical idea of economic rationality. This paper suggests ways in which the outcomes of Data Envelopment Analysis-type efficiency models can be rationalised. To illustrate the concepts we consider a data set of Canadian bank branches. The empirical results are encouraging since what appears to be inefficiency in some branches can be argued to be the outcome of rational decisions regarding resource allocation.

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)0.016
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.003
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0030.001
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 head0.116
GPT teacher head0.397
Teacher spread0.282 · 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