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Record W2164067112 · doi:10.1177/0008417414533185

Survivors of brain injury: The narrative experiences of being a college or university student

2014· article· en· W2164067112 on OpenAlexvenueno aff
Susan Cahill, Jamie M. Rotter, Kara K. Lyons, Antonina R. Marrone

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2014
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativePsychologySet (abstract data type)Qualitative researchTraumatic brain injuryOccupational therapyMedical educationGrounded theoryClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The deficits associated with a brain injury may pose many challenges to young adult students. PURPOSE: The purpose of this study was to conduct an in-depth exploration of the experiences and processes individuals who self-identify as having a brain injury go through during college or university to overcome obstacles. METHOD: This study used a basic interpretative qualitative design. Data were collected through semi-structured interviews and analyzed with the constant comparative method. FINDINGS: Three themes emerged: balancing act, reality versus injury, and square peg in a round hole. Participants discussed personal strategies that they used to help them be successful. Despite these strategies, the participants continued to feel out of place and felt that seeking disability services would further set them apart from their non-injured peers. IMPLICATIONS: Individuals post-brain injury may benefit from occupational therapy services to reduce the challenges associated with functioning in the student role in college and university environments.

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)0.003
metaresearch head score (Gemma)0.008
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: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0090.009
Scholarly communication0.0050.004
Open science0.0020.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.136
GPT teacher head0.407
Teacher spread0.271 · 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

Citations14
Published2014
Admission routes1
Has abstractyes

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