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Record W7132937187

Remote Robotics, or the Digital Re-embodiment of Labout

2024· other· en· W7132937187 on OpenAlexaff
James Steinhoff, Julian Posada, Alessandro Delfanti

Bibliographic record

VenueTSpace · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsToronto Rehabilitation Institute
Fundersnot available
KeywordsRoboticsRobotRemote controlProcess (computing)Remote laboratoryTelerobotics
DOInot available

Abstract

fetched live from OpenAlex

The remote operation of robots in logistics is becoming increasingly prevalent, with robots being deployed across various sectors and operated by workers from a distance. This allows manual labour to be conducted remotely. Despite eliminating the need for physical proximity between the robot and the operator, remote robotics still necessitates human interaction to control the machinery, a process we call re-embodiment. This working arrangement introduces constraints on the communities and territories of remote workers. Rather than deviating from traditional labour practices, remote robotics extends the reach of capital and perpetuates existing patterns of exploitation.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.100
Threshold uncertainty score0.336

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0050.008
Open science0.0010.006
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1000.023

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 head0.033
GPT teacher head0.346
Teacher spread0.312 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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