Bibliographic record
Abstract
How do we move things when it really matters? Drawn from research encounters, this article traces the journey of blood from donor to recipient through nine fictionalized vignettes interwoven throughout the article. This article makes two key contributions. First, by using blood as both exemplar and metaphor, this article experiments with fictionalized vignettes to illustrate the ‘non-visible . . . non-obvious . . . non-verbal’ vein-to-vein journey entailed in blood donation as a vital mobility. Blood supply chains rely upon and constitute complex and geographically expansive infrastructure circuits. Blood has a societal circulation and can be described as hemosocial. Second, it introduces and theorizes the concept of vital mobilities, extending Adey’s work on emergency mobilities. I distinguish vital mobilities in two ways: they are non-optional material and/or energetic movements that safeguard life, and they constitute ongoing circuits of care that can be ramped up in case of wide-spread crisis, and are also required in everyday contexts. Overall, this article contributes to cultural geography by demonstrating how non-traditional qualitative methods can effectively be used to represent and communicate dynamic temporalities, spatialities and rhythms of vital mobilities such as blood.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".