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Record W2889740410 · doi:10.1080/23800127.2018.1515335

Circulating blood: a conversation between Stephanie Sodero and Richard Rackham on vital mobilities in the UK

2018· article· en· W2889740410 on OpenAlexfundno aff
Stephanie Sodero, Richard Rackham

Bibliographic record

VenueApplied Mobilities · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMobilitiesConversationVital signsBlood donorDonationEveryday lifeSociologyMedia studiesMedicineSocial scienceLawPolitical scienceAnesthesiaCommunication

Abstract

fetched live from OpenAlex

Vital mobilities are goods that impact one’s life chances and that cannot be dematerialized. They must circulate externally in order to allow vital bodily circulations. Blood is a compelling and vital mobile material. It circulates impressive distances internally, within the body, and externally through the practices of donation and transfusion.This interview is organized in three parts. First, we learn about the everyday mobilities entailed in blood between the point of donation and the point of care. Second, we discuss three exceptional events that impacted NHS Blood and Transplant: the Manchester bombing, the London Olympics and the Filton Flood. Finally, we conclude by reflect on how social science might inform a research relationship between academic theorization of vital mobilities, which centres on the question, “How do move things when it really matter?” and the applied work of NHS Blood and Transplant.

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)0.015
metaresearch head score (Gemma)0.028
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: none
Teacher disagreement score0.101
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0320.031
Scholarly communication0.0130.016
Open science0.0020.009
Research integrity0.0120.021
Insufficient payload (model declined to judge)0.0070.001

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 head0.023
GPT teacher head0.235
Teacher spread0.212 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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