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Record W2226065040 · doi:10.1177/0263775815598156

Anxiety and phantasy in the field: The position of the unconscious in ethnographic research

2015· article· en· W2226065040 on OpenAlexaff
Jesse Proudfoot

Bibliographic record

VenueEnvironment and Planning D Society and Space · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsUnconscious mindPsychoanalytic theoryReflexivitySociologyEthnographyPsychoanalysisEpistemologyField (mathematics)PsychologySocial scienceAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

This article contributes to the geographical literature on reflexivity by asking what it means to take the researcher’s unconscious seriously in ethnographic research, and proposes psychoanalysis as a theoretical and methodological resource for researching the unconscious dimensions of fieldwork. I begin by describing three moments from my fieldwork with panhandlers and drug users that evince the operation of the unconscious. I then review psychoanalytic work in the social sciences where the researcher becomes the object of analysis and situate the debate on psychoanalytic methodology as an extension of earlier work on reflexivity by feminist geographers. I outline three methods for investigating the unconscious dimensions of fieldwork: analysis, supervision, and case consultation. Summarizing my experiments with these methods, I discuss: the discovery that key elements of my research were inextricably connected to my own anxieties as a researcher, how analysis of a dream from early in the fieldwork revealed phantasies rooted in childhood and a profoundly ambivalent relationship to my informants, and I propose a dialectical method for incorporating the revelations of psychoanalytic reflexivity into research. I conclude by discussing some of the possibilities and consequences of taking the unconscious dimensions of fieldwork seriously.

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)0.015
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.199
GPT teacher head0.484
Teacher spread0.285 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations26
Published2015
Admission routes1
Has abstractyes

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