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Record W2912497503 · doi:10.1080/14616688.2018.1558455

‘Motherhood capital’ in tourism fieldwork: experiences from Arctic Canada

2019· article· en· W2912497503 on OpenAlexaboutno aff
Roslyn Kerr, Emma Stewart

Bibliographic record

VenueTourism Geographies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyReflexivityIndigenousTourismContext (archaeology)Gender studiesValue (mathematics)Social capitalHabitusCultural capitalSocial sciencePolitical scienceGeography

Abstract

fetched live from OpenAlex

Drawing on a study of resident attitudes toward tourism development in the Canadian Arctic, this article examines the experiences of one of the authors who was accompanied by her infant son during her fieldwork. Utilising Lo’s (Sociological Perspectives 59(3):694–713, 2016) concept of ‘motherhood capital’, derived from the work of Pierre Bourdieu, we argue that the presence of her son, who joined her on five occasions between the age of 9 and 22 months, disrupted normal research roles and relationships. We describe how her son helped rather than hindered her acceptance into the Inuit communities where she was working. By using Bourdieusian theory to examine researcher experience, we move beyond the descriptive accounts that often dominate methodological discussions. Instead we aim to demonstrate the value of applying theory that is normally only used to examine encounters observed during fieldwork, to include analysing the researcher’s access and interactions. Due to the child-centred nature of the communities and the shared common ground of parenthood, we propose that Stewart’s demonstration of motherhood had the effect of dismantling several of the barriers some researchers face when entering communities for the first time. Motherhood capital facilitated her privileged access to the field and changed her perceived status from an outside researcher to an equal-status mother. This was particularly important in an indigenous context where she was always going to be seen as ‘other’. Drawing on extensive journal entries, this article adopts a reflexive approach to explore the influences her infant had on her experiences in the field.

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)0.005
metaresearch head score (Gemma)0.008
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 score0.058
Threshold uncertainty score0.340

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0580.019
Scholarly communication0.0070.002
Open science0.0030.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.249
Teacher spread0.240 · 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

Citations11
Published2019
Admission routes1
Has abstractyes

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