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Record W2017962074 · doi:10.1080/07408170903113789

Can flexibility be constraining?

2009· article· en· W2017962074 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

VenueIIE Transactions · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicScheduling and Timetabling Solutions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStaffingFlexibility (engineering)WorkforceRobustness (evolution)Operations managementBusinessIndustrial organizationComputer scienceEconomicsOperations researchMicroeconomicsEngineeringManagementEconomic growthChemistry

Abstract

fetched live from OpenAlex

Five common options for workforce flexibility and their robustness under uncertain demand are investigated. In the first stage, a firm makes optimal staffing decisions according to estimated demand and a given workforce flexibility policy. In the second stage, it reallocates its workforce to react to demand shocks. Numerical results are presented that show that flexibility can lead a firm to staff with too little slack to be flexible to demand shocks, thus leading to higher total costs, i.e., staffing and inventory costs. The forms of flexibility that give robust benefits are identified and an analysis on how different forms of flexibility interact with each other is performed. [Supplemental materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following supplemental resource: Appendix with additional tables of results.]

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.863
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.228
GPT teacher head0.425
Teacher spread0.197 · 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