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Record W2263517579 · doi:10.1080/1057610x.2016.1117325

Political Resilience to Terrorism in Europe: Introduction to the Special Issue

2015· article· en· W2263517579 on OpenAlexaboutno aff
Leena Malkki, Teemu Sinkkonen

Bibliographic record

VenueStudies in Conflict and Terrorism · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
Fundersnot available
KeywordsTerrorismPoliticsResilience (materials science)Political scienceCriminologyPsychologyComputer securityEngineeringComputer scienceLawPhysics

Abstract

fetched live from OpenAlex

Zambia is now one of the poorest countries in Sub-Saharan Africa.It is a land-abundant but sparsely populated country of 11 million inhabitants.This paper attempts to explain why the Zambian state has remained resilient over the period 1960-2010 despite confronting a substantial set of crises and unfavourable 'initial conditions', which include: one of the worst declines in per capita income in sub-Saharan Africa since 1970, a heavy debt burden, dramatic price and production declines in its main export (copper), one of the continent's most unequal distributions of income, one of the worst HIV/AIDS epidemics in the world, declines in its Human Development Index in every decade since 1980, relatively high levels of poverty, substantial influxes of refugees (particularly in the 1990s) that reached as high as 200,000, high transport costs as a result of being a landlocked economy, and being surrounded by five countries that have experienced civil wars and political disorder.By any conceivable measure, the growth performance of Zambia has been poor (see Table 1).Zambia's long-run trajectory of economic decline is closely related to the dramatic decline in its main industry, copper.In 1969, Zambia was the largest producer of copper among developing countries, and the third largest producer after the United States and the former USSR, with production twelve percent of world production.By 1990, Zambia produced only five percent of world production, compared to Chile and the United States each with eighteen percent; Canada eight percent, and the then-U.S.S.R. seven.Over the long term, exports declined from 622,900 metric tonnes in 1972 to 228,000 on the eve of privatisation in 1999.The decline in copper had reversed a dramatic five-fold increase in copper production in the period 1939-1960 under the colonial administration of Northern Rhodesia.At this time, copper production was under the control of the British Mining Company.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.072
GPT teacher head0.396
Teacher spread0.324 · 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 designQualitative
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

Citations20
Published2015
Admission routes1
Has abstractyes

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