Introduction – Autoethnography and Beyond: Colonialism, Immigration, Embodiment, and Belonging
Bibliographic record
Abstract
Life Writing’s choice to feature twenty-first century autoethnography offers interpretive, analytic, interactive, performative, experiential, and embodied forms of constructed self and culture in writing around the globe. It captures a broad range of autobiographical and anthropological intersections shared from Australia, Canada, China, Egypt, Turkey, and the USA in two parts. This first issue ‘Autoethnography and Beyond: Colonialism, Immigration, Embodiment, and Belonging,’ gathers recent applications of autoethnography as a decolonising and dehegemonising practice in the allegedly post-racial, post-colonial, and post-(hetero)sexist twenty-first century. Derived from colonial populations in which peoples have been systematically denied by modern anthropology the ability to record their experiences and explore the subjectivities, in their own voices, autoethnographic practices referred to as ‘native ethnography’ emerged as a post-colonial practice enabling subjects to engage with their representers on their own terms ( Pratt 1992 , 7). The continued expansion of autoethnography’s applications in the twentieth century showed ethnographers’ first efforts to acknowledge their presence as narrators of their fieldwork accounts. Deemed ‘autobiographical ethnography,’ the hybrid genre gave way to cultural anthropologists’ experimentation with interjecting self-exploration into their ethnographic writing ( Reed-Danahay 1997 , 2). Tracts of detailed ‘thick description’ in which they narrated their observations of their subjects’ cultures gave way to mutually biographical cultural explication in which the interpretive and experiential lens of the narrative of the anthropologist’s subjectivity became more transparent ( Geertz 1973 , 15). This new form reframed the authority of the ethnographer’s knowledge as second to that of the populations their representations had marginalised and took the first steps toward acknowledging the ideological hegemony of anthropologists ‘speaking for’ their subjects of investigation. In this issue, the innovative forms of resistance to dominant forms of representation include critiques of the academic job market, caregiving, parenthood, and museum curation where this issue’s contributors problematise the paradigms of insider/outsider, work/family, and spectacle/spectator with critically self-reflective accounts of our human condition in its embodiment and need for belonging.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".