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Record W4380266529 · doi:10.1515/9780228012290

Search for the Unknown

2022· book· en· W4380266529 on OpenAlexaboutno aff
Matthew Hayes

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2022
Typebook
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsInformation retrievalComputer science

Abstract

fetched live from OpenAlex

Beginning in the 1950s, alleged sightings of unidentified flying objects in Canadian skies bred tension between the state and its citizens. While the public demanded to know more about the phenomenon, government officials appeared unconcerned and unresponsive. Suspicion of government deepened among certain sectors of Canadian society in the decades that followed, leading to demands for greater public transparency and a new kind of citizen activism. In Search for the Unknown Matthew Hayes uncovers the history of the Canadian government’s investigations into reports of UFOs, revealing how these reports were handled, deflected, and defended from 1950 to the 1990s. During this period Canadians filed more than 5,000 reports of UFO sightings – many with striking descriptions and illustrations – with branches of government and law enforcement. Although the government conducted some exploratory studies, officials were unable to solve the mystery of UFOs or provide satisfactory answers about their alleged existence, and they soon declared the matter closed. Dissatisfied citizens responded by taking matters into their own hands, starting UFO clubs and civilian investigation groups, and accusing the government of a cover-up. A mutual mistrust developed between citizens who were suspicious of their government and officials who dismissed their fears and anxieties. This provided fertile ground for anti-authoritarian attitudes and the cultivation of conspiracy theories. In an era of political division, and amid heightened awareness of states’ responsibilities for their citizens, Search for the Unknown reveals the challenges that governments face in responding to public anxieties and preserving trust in public institutions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.092
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0180.026
Scholarly communication0.0140.022
Open science0.0020.009
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0370.012

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 head0.038
GPT teacher head0.279
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2022
Admission routes1
Has abstractyes

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