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Record W2090142706 · doi:10.3109/02699051003789252

Perceptions of traumatic brain injury network participants about network performance

2010· article· en· W2090142706 on OpenAlexafffund
Marie‐Ève Lamontagne, Bonnie Swaine, André Lavoie, François Champagne, Anne-Claire Marcotte

Bibliographic record

VenueBrain Injury · 2010
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsInstitut National d'Excellence en Santé et en Services SociauxUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationCentre hospitalier universitaire de Québec
FundersCanadian Institutes of Health Research
KeywordsPerceptionPsychologyTraumatic brain injuryApplied psychologyNetwork performanceCognitionKnowledge managementComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Networks have been implemented within trauma systems to overcome problems of fragmentation and lack of coordination. Such networks regroup many types of organizations that could have different perceptions of network performance. No study has explored the perceptions of traumatic brain injury (TBI) network participants regarding network performance. OBJECTIVE: To document the perceptions of TBI network participants concerning the importance of different dimensions of performance and to explore whether these perceptions vary according to organization types. METHODOLOGY: Participants of network organizations were surveyed using a questionnaire based on a conceptual framework of performance (the EGIPSS framework). RESULTS: Network organizations reported dimensions related to goal attainment to be more important than dimensions related to process. Differences existed between the perceptions of various types of network organizations for some but not all domains and dimensions of performance. CONCLUSION: Network performance appears different from the performance of an individual organization and the consideration of the various organizations' perceptions in clarifying this concept should improve its comprehensiveness and its acceptability by all stakeholders.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.068
GPT teacher head0.371
Teacher spread0.303 · 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 teacher head, not a consensus.

Study designObservational
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

Citations6
Published2010
Admission routes2
Has abstractyes

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