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Record W2983736639 · doi:10.1111/awr.12174

Emotional Labor On and Off Water

2019· article· en· W2983736639 on OpenAlex
Sharon R. Roseman

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAnthropology of Work Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCrewArgument (complex analysis)Emotional laborFeelingCommercializationParticipant observationOrder (exchange)ReproductionSociologyBusinessPsychologySocial psychologyEngineeringMarketingAeronauticsSocial scienceFinance

Abstract

fetched live from OpenAlex

Abstract This article focuses on the emotional labor requirements of crew working within the intra‐provincial ferry system in Newfoundland and Labrador, on Canada's North Atlantic coast. The argument draws on fieldwork interviews with crew and passengers, participant observation on the most intensive daily maritime commuting route in the province, and documentary sources. It builds on the theoretical framework first laid out by Arlie Russell Hochschild in her 1983 book The Managed Heart: Commercialization of Human Feeling. As is the case of examples of emotional labor in other economic sectors, the crew working in this public transportation system regularly modulate their own emotional reactions in order to interact effectively with passengers and coworkers who are often contending with frequent delays and uncertainties in this ferry system, which can be considered an example of precarious aquamobility.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.022
GPT teacher head0.373
Teacher spread0.351 · 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