MétaCan
Menu
Back to cohort
Record W4206649759 · doi:10.1353/wlt.2018.0012

Adventures in Memory: The Science and Secrets of Remembering and Forgetting by Hilde Østby Ylva Østby

2018· article· en· W4206649759 on OpenAlexaboutno aff
Anna Paterson

Bibliographic record

VenueWorld Literature Today · 2018
Typearticle
Languageen
FieldComputer Science
TopicCognitive Computing and Networks
Canadian institutionsnot available
Fundersnot available
KeywordsSeahorseForgettingPsychologyAdventureCognitive scienceHistoryCognitive psychologyArt historyBiologyZoology

Abstract

fetched live from OpenAlex

Hilde Østby & Ylva Østby Adventures in Memory: The Science and Secrets of Remembering and Forgetting Trans. Marianne Lindvall. Vancouver. Greystone Books. 2018. 312 pages. It sounds like a lovely pastime, diving to observe sweetly absurd-looking seahorses (genus Hippocampus), but what is its relevance to a book about memory? For this is indeed a wide-ranging book about how we remember past experiences and so also can predict the likelihood of future events. The Østby sisters—Hilda is a journalist and historian of ideas, Ylva a neuropsychologist— focus on human memory, though they can’t resist digressing now and then to tell us about, say, the uncanny ability of birds to memorize and adapt their songs or of slime molds to learn how to navigate mazes. Nothing about what seahorses remember , though, but instead a lot about the hippocampal gyri, a paired, deeply buried structure of rolled-up cortex in the vertebrate brain. Each hippocampus (it actually looks not so much like a seahorse, more like a tapering sausage) acts together with adjacent cortical areas to drive the consolidation of experiences into memory traces. Damage to one hippocampus is not incapacitating, but the loss of both seriously impairs memory retention for more than the few minutes of the short-term memory span. We are given a fascinating, if brief and somewhat eclectic, account of how the hippocampus works and connects to brainwide networks, but the writers are more at home with the psychological aspects of memory. They review hypotheses about why we can’t remember childhood events and then widen the discussion to the role of autobiographical (episodic) memory: so central to self-awareness yet some people manage with very little—how is that possible ? Why do we create persistent false memories of experiences we haven’t had (problematic for the police and the courts, for a start)? They confirm the everyday observation that memory is context dependent —“Where have I been before missing my car keys?”—and relate this to the hippocampal networks that encode place and direction of movement. Place- and direction-sense turn up again in answers to the question, “How can I improve my memory?” as professional “memory performers,” including actors and musicians, discuss their techniques. The rest of us are reminded, kindly, that forgetting can be a kind of benign pruning of the retention system. Only brief mentions are made of pathological variants of forgetfulness, as in attention deficit disorder , clinical depression, or dementia. Overall, the scientific and clinical material is solidly researched but brought alive in personalized anecdotes and in sisterly discussions. They write with such a persuasive mixture of intelligence, enthusiasm, and charm that occasional irrelevances (those seahorses) and too-long chatty passages merge into the engrossingly readable, thought-provoking whole. Anna Paterson House of Glack, United Kingdom Name Me a Word: Indian Writers Reflect on Writing Ed. Meena Alexander. New Haven, Connecticut. Yale University Press. 2018. 410 pages. The poet and critic Meena Alexander begins her introduction to the anthology Name Me a Word with a personal anecdote about her encounter with the novelist Raja Rao. Rao spoke about the “invented English ” he had gradually perfected with practice . The word “invented” provides a key entry point into the major concerns of this timely anthology of more than a century of major Indian writers reflecting on writing. Alexander deftly sidesteps the wornout clichés that permeate discussions of the “alienness” of English versus the “authenticity” of Indian languages. Indeed, World Literature in Review 90 WLT NOVEMBER–DECEMBER 2018 ...

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.005
GPT teacher head0.225
Teacher spread0.220 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueWorld Literature TodaySame topicCognitive Computing and NetworksFrench-language works237,207