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Record W4205434673 · doi:10.12987/9780300235050

Invisible Countries

2019· book· en· W4205434673 on OpenAlexaboutno aff
Joshua Keating

Bibliographic record

VenueYale University Press eBooks · 2019
Typebook
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsGovernment (linguistics)Political scienceReservationPolitical economyGeographyHistoryLawDevelopment economicsSociologyEconomics

Abstract

fetched live from OpenAlex

A thoughtful analysis of how our world’s borders came to be and why we may be emerging from a lengthy period of “cartographical stasis” What is a country? While certain basic criteria—borders, a government, and recognition from other countries—seem obvious, journalist Joshua Keating’s book explores exceptions to these rules, including self-proclaimed countries such as Abkhazia, Kurdistan, and Somaliland, a Mohawk reservation straddling the U.S.-Canada border, and an island nation whose very existence is threatened by climate change. Through stories about these would-be countries’ efforts at self-determination, as well as their respective challenges, Keating shows that there is no universal legal authority determining what a country is. He argues that although our current world map appears fairly static, economic, cultural, and environmental forces in the places he describes may spark change. Keating ably ties history to incisive and sympathetic observations drawn from his travels and personal interviews with residents, political leaders, and scholars in each of these “invisible countries.”

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)0.000
metaresearch head score (Gemma)0.001
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 score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0270.006

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 head0.252
Teacher spread0.223 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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