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Investigation of Remote Work for Aerospace Systems Engineers

2021· article· en· W3200729453 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

VenueINCOSE International Symposium · 2021
Typearticle
Languageen
FieldEngineering
TopicSystems Engineering Methodologies and Applications
Canadian institutionsCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsAerospaceWork (physics)Context (archaeology)Systems engineeringComputer scienceEngineering managementEngineeringKnowledge managementProcess managementAerospace engineering

Abstract

fetched live from OpenAlex

Abstract In many industries, remote work is becoming increasingly common. The global COVID‐19 pandemic has accelerated this shift, which poses a particular challenge to aerospace systems engineers (ASEs). ASE work is complex, consisting of a number of tasks that are traditionally largely conducted in‐person. Little literature exists to establish a basic understanding of remote work in the context of aerospace systems engineering development projects. This paper presents the results of an interview study, where hypotheses are explored to provide initial understanding of remote work in this context, and to motivate future studies. Analysis revealed: Design reviews experienced both challenges and benefits; Remote work has complicated collaborative work with artifacts; Assembly, Integration and Testing activities experienced significant challenges; Solutions have been thought of or implemented by ASEs, in particular the use of Slack and strategies managers may use to support their team members. Several additional research questions are motivated.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.723
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.034
GPT teacher head0.257
Teacher spread0.224 · 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