MétaCan
Menu
Back to cohort
Record W3178222712 · doi:10.29173/mocs181

Key Considerations before Integrating Modular Construction: Adaptation to the Traditional French Construction Processes

2015· article· en· W3178222712 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.

venuePublished in a venue whose home country is Canada.
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

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsnot available
Fundersnot available
KeywordsModular designModular programmingProcess managementComplementarity (molecular biology)Computer scienceProcess (computing)Key (lock)Modularity (biology)Order (exchange)Operations managementBusinessEngineering

Abstract

fetched live from OpenAlex

Industries around the world are improving continuously. They are converted into more efficient, dynamic and productive forms and construction is no exception to this principle. Indeed, this sector had started to get organized during the last decades. Modular design was introduced as an industrialization mean. However, few companies benefit from this concept in order to offer competitive prices and sustainable buildings. This paper, based on two case studies, presents key considerations for a successful implementation of modular design into an existing traditional construction business. Investigations were conducted to analyze the potential synergy and complementarity between modularization and the traditional French construction. The results show that modularization is viewed as a major change in the core business. As a consequence, modularization should be accompanied with a change management process. The results also revealed that modular construction goes hand in hand with a strong focus on technical frameworks. However, during the first implementation phase, spotlights should be slightly more directed into organizational planning and managerial postures.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.003
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 head0.029
GPT teacher head0.199
Teacher spread0.170 · 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