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Record W3028382750 · doi:10.1080/09658211.2020.1762896

The word length effect in backward recall: the role of response modality

2020· article· en· W3028382750 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

VenueMemory · 2020
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsRecallRecall testFree recallPsychologySerial position effectModality (human–computer interaction)Modality effectWord (group theory)Cognitive psychologyShort-term memoryCognitionLinguisticsArtificial intelligenceWorking memoryComputer scienceNeuroscience

Abstract

fetched live from OpenAlex

In immediate serial recall, it is well known that participants are better at recalling short rather than long words. This benchmark memory effect, known as word length effect, has been observed numerous times in forward recall. However, in backward recall, when participants are required to recall items in the reverse order, contradictory findings have been reported. For instance, in some studies, the word length effect was abolished in backward recall, whereas in others it was maintained. In the present study, we investigated the role of response modality in accounting for this discrepancy. Our results showed that in forward recall, the word length effect is unaffected by response modality. In backward recall with a manual response (click or written), the word length effect is as large as in forward recall. Critically, when participants recalled a word orally, the word length effect was severely reduced in backward recall. We concluded that response modality interacts with the processes called upon in backward recall.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.274
Teacher spread0.245 · 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