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Record W4379523288 · doi:10.1177/14661381231175853

Close quarters. Sailing the murky waters of an ethnography ‘at-home’

2023· article· en· W4379523288 on OpenAlexaff
David Sanson

Bibliographic record

VenueEthnography · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsEthnographySociologyIdentity (music)Gender studiesPosition (finance)Media studiesAnthropologyAesthetics

Abstract

fetched live from OpenAlex

This paper examines the tensions, struggles, and opportunities of doing ethnographies ‘at-home’. For the purpose of his PhD dissertation, the author returned to the city where he grew up, one of the biggest ports in France, with a strong maritime and industrial history. In this paper, the researcher reflexively recounts the social and personal springs of this longitudinal fieldwork among childhood friends and relatives in the working-class background from where he originates. While shedding light on the identity pressures that drove him to/through this research process, the author also addresses the profound emotional component of such investigation, as well as the difficulties of writing about it. Reflecting upon this singular experience, the paper eventually stresses how the researcher’s peculiar position influenced his methodological postures, determined the direction of his research questions and also how it ultimately provided robust original data and results, hereby asserting the strength of fieldwork conducted close to home for the production of critical and scientific social knowledge.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.009
Scholarly communication0.0060.006
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.194
GPT teacher head0.455
Teacher spread0.261 · 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.

Study designQualitative
DomainMethods
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

Citations2
Published2023
Admission routes1
Has abstractyes

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