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Record W2612244340 · doi:10.1111/area.12344

‘Maybe you will remember’: interpretation and life course reflexivity

2017· article· en· W2612244340 on OpenAlexafffund
Liesl L. Gambold

Bibliographic record

VenueArea · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsDalhousie University
FundersDalhousie UniversityEuropean Commission
KeywordsReflexivityInsiderInterpretation (philosophy)SociologyLife course approachEthnographyPerspective (graphical)Field (mathematics)EpistemologyAutoethnographyAestheticsGender studiesSocial sciencePsychologySocial psychologyVisual artsAnthropologyArtPhilosophyLinguistics

Abstract

fetched live from OpenAlex

This paper examines the relationship of the fieldworker, self‐proclaimed venerate ‘insider/outsider’, to their shifting role as researcher and traveller on the life course. Ethnographic fieldwork is a transitory research method, reliant on a gaze shifting from the breadth of the field site to the depth of individual human experience. The researcher is the conduit and the instrument of data collection but has not been adequately understood as a transforming agent in the process. Reflexivity is required to understand how the researcher's experiences and shifting position on the life course converge with fieldwork processes and data. Inspired by a phenomenological life course perspective I use data from fieldwork in Russia, Mexico and southern Europe to throw light on the emergent effects of life course shifts on the fieldworker's positionality and interpretation of research experiences and field notes. Researcher and textual reflexivity can result in a more vibrant recognition of the messiness of the human fieldwork experience and the resulting epistemological potential.

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)0.040
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.040
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0100.079
Scholarly communication0.0130.015
Open science0.0030.008
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.302
GPT teacher head0.580
Teacher spread0.277 · 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 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

Citations4
Published2017
Admission routes2
Has abstractyes

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