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Record W73025958

The World Until Yesterday: What Can We Learn from Traditional Societies? by Jared Diamond

2014· article· en· W73025958 on OpenAlexaboutno aff
Linda Quest

Bibliographic record

VenueInternational social science review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
Fundersnot available
KeywordsYesterdayPoliticsPopulationState (computer science)HomelandSociologyGovernment (linguistics)LawPolitical economyPolitical scienceMedia studies
DOInot available

Abstract

fetched live from OpenAlex

Diamond, Jared. The World Until Yesterday: What Can We Learn from Traditional Societies? New York: Viking, 2012. 512 pages. Hardcover, $36.00. Geographer Jared Diamond has done it again. In The World until Yesterday, the celebrated author of Guns, Germs, and Steel and Collapse has given us another thought-provoking and fascinating book. As in his previous writing, he brings together multiple disciplines, including anthropology, economics, sociology, political science, and psychology, to draw lessons from a pastiche of human cultures. Diamond's subjects live in traditional societies and in state societies, in bands, clans, tribes, chiefdoms, in WEIRD (Western, educated, industrialized, rich, democratic) societies, and more. They include Aboriginal Australians, Ache Indians, Aka Pygmies, iKung, Inuit, Nuer, and others, particularly New Guineans, whose homeland is Diamond's principle area of expertise. They differ. Some practice idiosyncratic customs, such as widow strangulation or elderly abandonment. Some allow children to play with sharp knives or fire, to wander off for days from home. Taken together, these subjects illuminate mantras of political science and justifications of government. People live in groups. They never completely agree. Conflicts are bound to arise. Diamond shows us that all societies have conflicts, but he argues that state societies are both necessary in a complex, population-dense world and advantageous--shown in words and movements of traditional individuals and peoples. Diamond summarizes: [A] prime concern of effective state government is to guarantee or at least improve public safety by preventing the state's citizens from using force against each other (p. 97). He also illuminates the legitimacy of Criminal Justice and of Peace and Justice Studies among the social sciences--the overriding goal of state is to maintain society's stability by providing a mandatory alternative to do-it-yourself justice (p. 99), and maintenance of peace within a society is one of the most important services that a state can provide (p. 98). The appreciation of persons for this is reflected in the ease with which they gave up thousands of years of practicing traditional war. The current of change at present is running from traditional societies to state societies. Hunter-gatherers and small-scale farmers aspire to a Westernized lifestyle and seek to enter the modern world. For his part, Diamond regularly visits Papua New Guinea, but has no intention of moving there. New Guineans themselves know the modern world offers huge advantages: state-imposed peace that they could not achieve for themselves, steel tools, material goods that make life easier, opportunities for formal education and jobs, access to information, access to a broad diversity of people, more rights for women, good health, effective health care, less violence, less danger, and more food security. The comparisons are perceptible to traditional villagers. WEIRD peoples have much longer lives and lower frequency of experiencing the deaths of their children. Nevertheless, traditional children are more self-assured, inventive, and mature, more capable of coping with challenges and dangers while still enjoying their lives more than WEIRD kids. Such considerations prompt the question in the subtitle--What can we learn from traditional societies? Also, how can we do it? To answer this question, Diamond focuses on the practices that suffer from collective behavior and societal action. …

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.566
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.002
Scholarly communication0.0010.001
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 head0.034
GPT teacher head0.316
Teacher spread0.282 · 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.

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
Published2014
Admission routes1
Has abstractyes

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