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Record W2740457034 · doi:10.1075/sibil.53.11cha

Bilingualism, cognitive reserve, aging, and dementia

2017· book-chapter· en· W2740457034 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStudies in bilingualism · 2017
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsMcGill UniversityConcordia University
Fundersnot available
KeywordsCognitive reserveDementiaNeuroscience of multilingualismPsychologyCognitionGerontologyCognitive impairmentMedicineNeurosciencePathology

Abstract

fetched live from OpenAlex

Abstract Research investigating the contribution of bilingualism to cognitive reserve has produced mixed findings. Previous reviews and commentaries have explored potential reasons for the inconsistent findings across studies, including language status, participant characteristics, and immigration-related variables. This chapter addresses several questions that have received relatively less attention. Specifically, in this chapter we aim to clarify the relationship between brain function and structure within a reserve framework (including data from our lab examining regional cortical thickness in patients with mild cognitive impairment and Alzheimer’s disease). We also review the impact of bilingualism on memory functioning, and examine theoretical and practical issues (such as trajectory of change in cognitive function) surrounding the cognitive reserve hypothesis. We end by discussing the potential for -and practicalities of- using Big Data initiatives to contribute insight into the role of bilingualism in cognitive reserve and brain function.

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.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.672
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.151
GPT teacher head0.399
Teacher spread0.248 · 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