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Record W2913984005

Behind breakdown: the case of the MV Veteran

2018· dissertation· en· W2913984005 on OpenAlexaboutno aff
Donny Harry Persaud

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2018
Typedissertation
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
Fundersnot available
KeywordsSituatedNorm (philosophy)Function (biology)EngineeringBusinessEnvironmental planningPublic relationsGeographyPolitical scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Infrastructure as a topic of research has seen much attention within geographic and
\nScience and Technology Studies literature. Frequently, studies of infrastructure explored
\nthe implementation of new infrastructures or the effects of infrastructural breakdowns on
\nthe relations sustained by these systems carrying the implicit assumption that
\ninfrastructures function seamlessly and disruptions constitute aberrations from a working
\nnorm. Recent works have problematized this assumption exploring the everyday practices
\nof infrastructure’s users and the practices of repair and maintenance which sustain
\ninfrastructural systems. This thesis examines breakdown, repair, and maintenance of a
\nnew passenger ferry operating in a rural island community off Newfoundland’s north
\ncoast. This thesis extends current observations on emerging repair and maintenance
\nliterature from the situated activities of maintainers to the decision-making processes
\ngoverning repair and maintenance. In doing so, this thesis illustrates how space,
\ncommonly held as a neutral surface on which these practices are undertaken, comes to
\ninfluence how the passenger ferry is repaired and maintained as well as used by the
\nislands’ residents.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0030.005
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.241
Teacher spread0.225 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

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