Motherlines, thin places and somatic orientations: An embodied inquiry
Bibliographic record
Abstract
In this article, I explore the role of ancestrally connected sites as places of somatic orientation and potentially as sites of embodied memory. Inspired by seeking connection with my Irish great-great-great grandmother, Jane O’Brian and her lineage, I travelled to Ireland as a North American woman, undertaking a circling journey to a land of my Motherlines. In this article, I explore touchstone moments on the land in Ireland, including my serendipitous stumble to the Hill of Tara in County Meath, Ireland. The article explores, in particular, the communication between my own body and particular places on earth, undergirded by other literature that explores human-land-based connection. I draw on the methodologies of embodied inquiry and autoethnography. Echoing and contrasting with the journeys of other writer–researchers who have engaged in their own ancestral journeys, I ask questions about land-based connections, and how these connections are challenged and remembered in the process of migration and uprooting. Acknowledging the possibility of nostalgic projection by diasporic returnees I touch on the potential pitfalls of such an exploration while weaving an autoethnographic and embodied inquiry which explores land-based connections as dynamic, multi-layered and a potential site of somatic re-orientation.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.044 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".