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Record W4205922315 · doi:10.12987/9780300216646-001

Acknowledgments

2020· book-chapter· en· W4205922315 on OpenAlexfundno aff
Rebecca Lemov

Bibliographic record

VenueYale University Press eBooks · 2020
Typebook-chapter
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
FundersUniversité de LausanneHome OfficeUniversity of TorontoJohns Hopkins UniversityUniversity of Pennsylvania
KeywordsGeography

Abstract

fetched live from OpenAlex

More than a decade ago, when I was living in Oakland, California, I was under the impression that if one found a book lying on the street or stacked in a free pile near the sidewalk, one should probably read it because it might carry a message.Indeed, I did so when I found the book The Captive Mind, by Czeslaw Milosz (1953), around the end of the last century, in a red jacket, abandoned on the sidewalk.In the book, Milosz describes the fate of "human materials," and this idea stuck with me through the end of graduate school, all sorts of life events, the early years of teaching, and the eight years it's taken me to write this book.Under particular conditions and certain systems, Milosz seems to say, humans function as both materials and living beings or as subjects and objects.My first book was about the constraint of human materials.This is a book about human materials also.The archive I'm calling the "database of dreams" was at its core a collection of just such materials-sometimes also called by their collectors "human documents"-and was part of a larger movement to collect the same.In the process of telling the story of the archive housing these documents and the lives they represent, I have incurred many human debts and drawn on many friendships.First are the people from around the world who contributed to the archive I've written about.These are the subjects whose stories and dreams I have referred to, drawn from, or retold in fragmented fashion.Most are deceased; many may not have known that their dreams or other materials were being stored in a social-scientific

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.926
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.170
Teacher spread0.119 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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