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Record W7164255739

Violent Impacts : How Power and Inequality Shape the Concussion Crisis (Edition 1)

2025· book· en· W7164255739 on OpenAlexaboutno aff
Kathryn Henne, Matt Ventresca

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2025
Typebook
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsConcussionInequalityPower (physics)AthletesSocial inequalityPoison controlPublishing
DOInot available

Abstract

fetched live from OpenAlex

<B>A free ebook version of this title is available through Luminos, University of California Press&rsquo;s Open Access publishing program. Visit <a href="http://doi.org/10.1525/luminos.241">www.luminosoa.org</a> to learn more</B>.<BR /><BR /> Concerns regarding brain injury in sport have escalated into what is often termed a &ldquo;concussion crisis,&rdquo; fueled by high-profile lawsuits and deaths. Although athletes are central figures in this narrative, they comprise only a small proportion of the people who experience brain injuries, while other high-risk groups&mdash;including victims of domestic violence and police brutality&mdash;are all too often left out of the story. In <I>Violent Impacts</I>, Kathryn Henne and Matt Ventresca examine what is and what isn&rsquo;t captured in popular discourse, scrutinizing how law, science, and social inequalities shape depictions and understandings of brain injury. Drawing on research carried out in Australia, Canada, and the United States, they illustrate how structural violence centers certain bodies as part of the concussion crisis while pushing others to the margins.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.255
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0100.009
Science and technology studies0.0010.002
Scholarly communication0.0060.009
Open science0.0040.011
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0110.000

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 head0.109
GPT teacher head0.381
Teacher spread0.272 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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