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Enregistrement W4234940323 · doi:10.1108/978-1-78769-919-920191031

Index

2019· paratext· en· W4234940323 sur OpenAlexaboutno aff

Notice bibliographique

Revuenon disponible
Typeparatext
Langueen
DomaineSocial Sciences
ThématiqueTerrorism, Counterterrorism, and Political Violence
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTerrorismIslamPublishingIndex (typography)Political scienceAl qaedaSocial scienceLawSociologyGeography

Résumé

récupéré en direct d'OpenAlex

Citation (2019), "Index", Das, R.C. (Ed.) The Impact of Global Terrorism on Economic and Political Development, Emerald Publishing Limited, Bingley, pp. 411-435. https://doi.org/10.1108/978-1-78769-919-920191031 Publisher: Emerald Publishing Limited Copyright © 2019 Emerald Publishing Limited INDEX Abuse forms of, 114 of human rights, 228 Academics, 382–383 Ad hoc military violence, 63 “Address to the Nation”, 85, 87 Advalorem rate, 8 Advance manufacturing sector, 7 Advanced countries. See Developed countries Afghanistan, terrorist events in, 97 Afro-centric approach, 270 “Age of Muslim Wars” (Huntington), 140 Aggregate demand function for defense services, 9 Agriculture development, 345 Aircraft self-protection systems, 144 Airplane hijackings, 224 AK-47s, 385 Akaike information criterion (AIC), 174, 196 Al Haramain Islamic Foundation, 89 Al Shaaba terrorists group, 275 Al-Qaeda, 75, 89, 116, 140–141, 143, 147, 149, 323, 357 Central, 329 functioning, 90 jihadi terrorist infrastructure, 145 militants, 84, 87 social media channels and Telegram, 112 See also 9/11 attacks Al-Qaeda in Islamic Maghreb (AQIM), 194, 323 Al-Sadaqah Organisation, 112 Al-Shabaab, 323 Al-Zarqawi, Abu Musa’ab, 86–87, 323 al-Zawahiri, Ayman, 323 Algebraic manipulation, 13–14 Algerian Salafi’s group, 194 “Almajiri”, 194 Alternative coins (altcoins), 126–127 America and Political Islam (Fawaz), 141 Annan, Kofi (United Nations Secretary General), 79 Anonymity, 134 Anti-Money Laundering (AML), 117, 121, 131 Anti-national activities, 36–37 comparative statics analysis, 41–43 effects of policy changes, 47–48 expressions of model, 45–46 model, 38–41 Anti-Sikh riots (1984), 253, 405 Anti-Tamil violence (1991), 254 Anti-terrorism measures, 28 policies in selected Asian countries, 211–214 Antiquity, 323 feminism and terrorism from, 327–328 Antiterrorism Act (ATA), 219–220 “Arab Spring”, 88, 156 Argentina, cryptocurrency in, 131 Armed conflict and terrorism, 187 Armed Forces Special Powers Act, 391, 393 Asia Asia-Pacific defense landscape, 88–89 empirical analysis, 215–219 GTI, 215 literature survey, 207–208 objective of study and methodology, 208–209 and Pacific countries, 173 policy measures to combat terrorism, 219–220 status of military expenditure and terrorism, 209, 210, 215 terrorist activity and anti-terrorism policies, 211–214 Asian insurgencies (1965), 332 Assassin (Islamic), 74 Assassinations, 224 Augmented Dickey–Fuller test (ADF test), 230, 282, 286 Autocratic regimes, 343 Automatic Teller Machines (ATMs), 119 Autoregressive distributive lag model (ARDL model), 240–241 ARDL-ECM model, 207–209, 215 bound test, 241–242, 299, 359–360, 364–365 Babri Masjid demolition riots (1992 and 1993), 405 Backward sector, 7 BADOOS Boys in Lagos, 354 Baduria riots (2017), 254 Bangladeshi fundamentalist terrorist groups, 142 Bank looting, 114 Banking techniques, 110 Bankura, SHGs progress of, 311–318 Barter system, 126 Battle of Algiers (1956–1957), 328 Bidirectional Granger causality, 372 Bilateral trade, 54 BILISA map, 102 bin Laden, Osama, 86–87 See also Al-Qaeda Binomial regressions, negative, 77 Bitcoin, 111, 126–133 Bivariate VAR structure, 55 “Black-washing”, 113 Blockchain mechanism, 128–130 Boko Haram (BH), 194, 237, 268, 294–295, 322, 327, 335 GBV and ideology, 332 ideology, 332–333 insecurity effects, 298–299 insurgency, 272, 297 and MNJTF, 271–273 suicide car bombing attack (2011), 323 Bolivia, cryptocurrency in, 131 Bolsheviks movement, 227 Bombings, 224 homicide, 324, 334 intentionally indiscriminate, 383 Madrid train bombing (1988), 226 Brazil, cryptocurrency in, 131 British Special Air Service, 329 Bush, George Jr., 85–86 Business cycle fluctuation, 168 C130J transport, 144 Cambodian Khmer Rouge, 332 Canada, cryptocurrency in, 131 Capital full-employment conditions, 40 inflow, 37 modernization, 282 Capital flight, 280 terrorism and, 282, 285 Capital stock, 36–37 accumulation, 37 economy’s productive, 38, 43 rate of productive utilization, 42 Cardano, 128 Cartogram maps, 106 Cash couriers, 111, 117 Causality analysis, 299 relationships, 196–197 Central Bank of Nigeria Statistical Bulletin, 358 Central Intelligence Agency (CIA), 88 CIA-sponsored study, 75 Charities, 89, 113–114, 118 Chile, cryptocurrency in, 131 China, cryptocurrency in, 131 Christopher, Warren, 141–142 Civic Action Program (CVP), 347 Civil conflict, 309 Civil liberties, 73, 79–80 Civilian JTF, 334 Civilization, 398 Clash of Cultures or Clash of Interests (Fawaz), 141 Cluster analysis, 25 Co-integration, 283–284 ARDL-bound testing approach to, 359–360 equation, 287 Coefficient of variation (CV), 313, 406–408 of women SHG, 314 Colombia, cryptocurrency in, 131 Combat roles, women in, 324, 332, 334–335 Combat terrorism, policy measures to, 219–220 Combating Terrorist Financing (CFT), 121 Commercial enterprise/entrepreneur model, 116 Commodities hard-to-trace, 117 high-value, 111, 117 Commodity Future Trading Commission (CFTC), 131 Communication, 50 Community Support Mechanism (CSM), 220 Comparative static analysis, 11, 13, 41–43 Complex multilateral post-Cold War foreign policy, 145 Compound annual growth rate (CAGR), 312, 315 Concentration index (CI), 65–66 Concentric circle, 268 Conflict, 75, 156–157 civil, 309 risk, 156 Conflict transformation (CT), 336 participation as CT initiators, 336 Contemporary terrorism in India literature survey, 225–226 model, 226 political factors, 228–229 results, 230–232 social factors, 229–230 socioeconomic factors, 226–228 Contemporary women terrorist groups, 328–329, 333–334 Control of corruption (CC), 344, 406–408 Convention on Prevention and Punishment of Terrorism, 380 Corporate investors, 36 Correlation analysis, 182–183 matrix, 311–312, 362 Corruption, 156, 197 in public distribution system, 309 Cost effects of terrorist activities, 294 Counter Financing of Terrorism policy, 131 Counter-Terrorism Committee (CTC), 120 Counter-Terrorism Committee Executive Directorate (CTED), 120–121 Countering Financing of Terrorism (CFT), 117, 220 Countering terrorist financing, 110, 119–122 Counterterrorism (CT), 86, 239, 274–275, 295, 299, 336 cooperation, 220 efforts, 280 programmes, 64 See also Terrorism Counterterrorism and Transnational Crime Unit (CTTCU), 220 Counterterrorism Cooperation Initiative (CCI), 149 Counterterrorist activities, 141–142 operations, 117 policies, 51 Country Reports on Terrorism (2016), 208–209 Countrywise perspective toward cryptocurrency, 130–132 Credit card fraud, 116 Credit-linkage schemes, 311, 314 Crimes, 36, 250, 255, 264, 380 economic theories, 36–37, 250 organizations, 114 property-related, 250–252, 258–264 violent, 251–252 war, 380 Criminalizations of politics, corruption, terrorism, 403 Cropping intensity (CI), 308, 317 Cryptocurrency, 129 bitcoin, 129–130 countrywise perspective toward, 130–132 history and evolution, 126 and link to terror finance, 134–135 and money laundering, 132–133 money laundering for drug dealing, 133–137 objectives of study, 127 research methodology, 127 and terror financing, 133–134 transactions, 127 types, 127–129 Cryptography, 127–128 Cumulative sum of recursive residuals (CUSUM), 216, 360, 366 Cumulative sum of squares of recursive residuals (CUSUMQ), 360, 366 Customs Service, 144 D Company, 149 Decentralized curriencies, 127, 132 Decentralized system, 129 Deception, 327 Decision Making Trial and Evaluation Laboratory (DEMATEL), 156, 158 Decision-making model, 160–162 Decremental deprivation, 227 Defense budget, 146, 282 Defense expenditure (DE), 88–89, 207, 281, 296, 299 Defense Policy Group (DPG), 143 Defense sector, 6, 7 model, 7–10 output levels, 11–12 prices, 16–19 welfare and augmentation of terrorism as externality, 10–11 Defensive countermeasures, 65 Defunct SHG (DSHGs), 313, 317 Democracy, 342–343, 402–404 Democratic principles, 77 Democratic regimes, 343 comparative study between non-democratic and, 80–81 Demonetization in India, 409 Descriptive analysis, 268–269 Deterrence, 28 Deutsch, Karl, 140–141 Developed and developing countries, 51, 53 macroeconomic impacts of terrorist activities in, 50–57 terrorism in, 97 Digital currency, 126, 129 transfer, 128 Digital economy, 127 Digital India, 408 Digital payment system, 126–128 Dispossession, 228 Distributed ledger, 129 District Rural Development Authority (DRDA), 315 Domestic investments, 207 Domestic investors, 168–169 Drought-prone region, SHGs progress in, 313–315 Drug money laundering of cryptocurrency, 133–137 trafficking, 114 violence in northwest India, 404 Dual defense sector, 7 E-governance, 407 Econometric exercises, 136–137 models, 27, 251, 256 theory, 256–257 Economic association between terrorism and development, 30 depression, 187–188 deprivation, 354 development, 24–25, 29, 342 equality, 76 factors, 226–227 inequality, 227 interpretation of results, 288 policies, 51, 168 setup, 236 theory of crime, 250 Economic Community of West African States (ECOWAS), 269, 271 Economic consequences of terrorism, 297–298 economic impacts of terrorism, 187–188 literature review, 181–182 terrorism and fatality in South Asia, 182–187 Economic growth (EG), 50–51, 53, 67, 181–182, 188, 207–208, 281, 300, 356–357 determinants, 52 terrorism impact, 52, 296 Economic impact and cost of violence in India, 391–392 of terrorism, 187–188, 385–386 Education, 36, 398 Eigenvalue stability condition, 199 El-Zakzakky, Sheikh Ibrahim, 194, 236 Electoral democracy in Northeast India, 345–346 Electronic payment systems, 111 Electronic warfare systems, 144 Empirical analysis, 54, 215 long-run associations among variables, 216–219 short-run associations among variables, 219 Endogenous variables, 301 Engel–Granger co-integration test results, 286–287 Enthusiasm, 272 Equality test, 312 Equilibrium condition of market for public defense service sector, 16 for non-traded public healthcare sector, 15 for private defense sector, 16–17 Eradication of terrorism, 85 Error correction model (ECM), 244, 284, 357 dynamic, 359 See also Vector error correction model (VECM) Error correction term (ECT), 209, 231 Ethereum (ETH), 128, 132–133 Ethereum classic (ETC), 128 Ethnic compilation, 157 conflicts, 180–181 power change, 157 rivalry/chauvinism, 194, 236 violence, 404 Ethno-nationalist terrorism, 404 Ethnonationalist terrorism, 76 Ethnopolitical violence, 180 Ethnoreligious violent activities, 198 European Commission, 157 Europol, 133 Exogenous shock, 39 Exogenous variables, 301 Experimental economics, 65 Export–Terrorism Index, 103 Extortion, 114 of money, 111 Extremism, 181, 219 Extremist, 75, 180 F-18 fighter-bomber, 144 F-statistic, 312 False trade invoicing, 111 Fascism: Past, Present, Future (Laquer), 72 FBI, 144 Fear-generating attacks, real targets of, 75–76 Federally Administered Tribal Areas (FATA), 186 Feldstein-Horioka model (FH model), 357 Female martyrs, 322 Feminism, 326 and terrorism from antiquity, 327–328 Final prediction error (FPE), 196 Financial Action Task Force (FATF), 111–112, 115, 121–122 Financial/finance, 110 attacking, 89 crisis, 207 economy, 280 techniques, 110 transactions, 128, 132–133 “Fire finder” counter-battery radar sets, 144 Fiscal effects of terrorism in Nigeria, 293–302 Five-Year Plan process (FYP process), 349 Fixed effect model, 173 Fledgling democracies, 77 Focused group discussions (FGDs), 325, 333 Foreign capital inflow, 280 Foreign direct investment (FDI), 6–7, 11, 13–14, 19, 26, 51, 63, 168, 207, 224, 236, 347, 350 ARDL bound test results, 242 ARDL model, 240–241 data and methodology, 239 estimation results, 242–243 flow, 52–53, 288–289 GTI, 238 inflow, 172, 237 model specification, 240 short-run dynamics of impact of terrorism on, 243–245 terrorism impact, 288–289, 297 test for stationarity, 241 theoretical framework, 239–240 Foreign exchange debts, 156 rates of developed countries, 27 Foreign investment and instability, decrease in, 187 Foreign Investment–Terrorism Index, 104 Foreign investors, 51, 168–169 Formal banking, 111 Formal financial systems, 111, 117 Formal sector labor market, 38 Four-sector general equilibrium trade model, 7 Fraction of capital input, 38–39 France and MNJTF, 271–273 “Free rider” problem, 64 Freedom of association, 72 Freedom of speech, 72 Fronte de Libération Nationale (FLN), 328 Fulani-Herdsmen attackers, 354 Full-employment conditions for labor and capital, 40 of resources, 9 Fund raising through social media, 116 transfer, 117 Fuzzy DEMATEL, 156, 158–159 Fuzzy linguistic scale, 158 Fuzzy matrix, 160 average, 158 normalized direct-relation, 159 total-relation, 159 Gas reservoirs, control of, 114 Gender equality, 338 Gender-based violence (GBV), 332 Generalized method of moments (GMM), 170, 256, 258 Geo-stationary Launch Vehicle (GSLV), 148 Geostatistics, 100 Germany, cryptocurrency in, 130–131 “Geronimo Thrust 02”, 144 GINI, 233 coefficient, 229–230, 252 index, 226, 228 Global Business Policy Council, 168 Global Community Engagement and Resilience Fund (GCERF), 220 Global conflict risk determinants, 156–158 factors, 156, 160–161 index, 156, 157, 160–161 Global Counterterrorism Forum (GCTF), 149 Global Index of Terrorism, 25 Global Law Enforcement Agencies, 132–133 Global Politics (Heywood), 72 Global terrorism, 384–385 impact, 385–386 Global Terrorism Database (GTD), 52, 110, 172, 196, 240, 295, 312, 358, 384, 389–390 Global Terrorism Index (GTI), 23, 97, 191–192, 208, 215, 238, 386, 390 in India, 389–390 report, 65, 180, 294 score, 65–66 Global War on Terror (GWOT), 75, 85, 86, 206 declaration, 85 expected outcomes or successes, 86–89 objectives, 92 unexpected outcomes, 89–93 Globalization, 114 terrorism in backdrop of, 79–80 Godhra Kand. See Gujarat riot Godhra riots (2002), 254, 405 Good governance India, 403–404 women empowerment, 409 Good Governance Day, 408 Governance, 402 impact, 356 Government counterterrorism allocation, 64 expenditure, 300 government-owned service sector, 38 group, 140 revenue, 297, 299–300 Government effectiveness (GE), 344, 406–408 Government of India (GOI), 347 Granger causality analysis, 181–182 Wald tests, 196–197 Gross domestic product (GDP), 25–26, 50, 65, 67, 97, 172 GDP–Terrorism Index, 102, 106 growth rate, 208 high-GDP economies, 67 per capita growth, 208 Gross domestic product per capita (GDPPC), 358, 372 Growth estimation, 312 effect of terrorism in Nigeria, 293–302 “Guantanamo Bay and Abu Gharib” incident in Cuba, 90–91 Guardian, The , 326 Guerilla attacks, 346 Gujarat riot (1969), 253, 405 Gurr, Ted Robert, 229 Handbook of Statistics on Indian Economy , 285–286 Hannan–Quinn (HQ), 196 Hannan–Quinn criterion (HQC), 242 Haqqani Network, 149 Harakat-ul-Mujahadeen (Islamic freedom fighters), 387 Haram, Boko, 354 Hard fork, 128 Hausman test, 173 Have and Have-not hypothesis, 355 Hawala system, 111, 118 Head count ratio (HCR), 31 Health and stress, 188 Heckscher–Ohlin–Samuelson model (HOS model), 37 Heteroscedasticity and autocorrelation (HAC), 245 High-high regions, 100 High-low regions, 100 Hijbul Mujahideen, 387 Hizb-ul-Mujahideen, 148 Homicide(s), 250 bombing, 324, 334 elasticity estimate of, 259–264 Horizontal FDI, 172 HUJI groups, 145 Human development factors, 252 and terrorism, 184 Human Development Index (HDI), 226, 229–230 Human loss, 182 Human rights abuses, 228 denial of, 397–398 violations, 228, 336 Human trafficking, 114 Humiliation, 228 Hussein, Saddam, 90, 98, 144–145 Ba’athist government removal, 90 Hyderabad riots (1990), 253 Hypothetical statement, 72 Ideological backup, 194 Idriss, Wafa (female suicide bomber), 322 Illegal activities, 132–133 Illicit taxation of goods and cash, 114–115 Im, Pesaran and Shin method (IPS method), 54, 56 Imperialism, 133–134 Impulse response function (IRF), 195, 197–198 Incapacitation, 28 Income distribution, 13–14 inequality, 36, 158, 356 Independent People of Biafra (IPOB), 354 India, 140 co-integration, 283–284 cryptocurrency in, 131 data, 285–286 democratic experience, 402 ECM, 284 economic impact and cost of violence, 391 economic interpretation of results, 288 Engel–Granger co-integration test results, 286–287 good governance, 403–404 GTI in, 390–391 incidence of military expenditure and terrorism in, 281–282 Johansen’s co-integration test results, 287 measures to strengthening administration, 407–409 methodology and data, 282 relationship between FDI flow and terrorism, 288–289 relationship between terrorism and foreign capital inflow, 280 special laws on terrorism, 391–397 steps to tackling problem, 409–410 terrorism and human loss in, 184–185 terrorism and military expenditure, 280 terrorism in, 387–389, 404–405 terrorism-prone regions, 290 terrorist events in, 97, 389–390 testing for stationarity of data, 282–283 unit root test results, 286 VECM, 284–285, 287–288 view on terrorism in South Asia, 142 worldwide governance indicators in Indian context, 405–407 India’s Foreign Policy: Challenge of Terrorism, Fashioning New Inter-state Equations (Dixit), 141 Indian economy, 347 Indian Express , 143 Indian Foreign Policy (Ganguly), 141 Indian Navy, 146 Indian Ocean Rim (IOR), 146 Indian political structure, 344 Indian Space Research Organization (ISRO), 148 Indian stock markets, 27 Indirect costs effects of terrorist activities, 294 Indirect social utility functions, 11 Indo-US changing relational pattern, 141 Counterterrorism Joint Working Group, 145 engagement, 147–148 Joint Working Group, 144, 147 relations post 9/11 incident, 141 strategic 146 63, 357 227 index, 358 social 251, 226 variables, 355 rate, 358 sector labor market, 38 systems, 111 131 development 128 prices, of and 23, 385 in approach, 156 violence, 383 383 Intelligence 75, and data and methodology, economic effects, results, See also Terrorism approach, 342 systems, 131 92 Country 301 92 investment 36 112 politics, 84, 326 terrorism, 140–141, 170, 181, See also Joint policy trade 54 and 111 political and, 131 of 74 142 90 terrorist events in, 97 329 77 Islamic banking, 118 111 140–141 141–142 Islamic African 89 in Nigeria, 322 terrorism, 74 Islamic of and See Islamic of and Islamic of and See Islamic of and Islamic of and 90, 110, terrorist group, 327 28 conflict (2002), 326 387 90, 143, 149, 387 See Boko Haram 387 and incidence of terrorism in, terrorist violence in, cryptocurrency in, 402 322 112 terrorism, 404 Johansen’s co-integration test, relationship between FDI flow and terrorism, 288–289 results, 287 Johansen’s test, Joint 148 Joint on terrorism, Joint policy policy toward 147 India’s view on terrorism in South Asia, 142 Indo-US engagement, 147–148 148 on terrorism, 145 and exercises, 144–145 literature review, 141 terrorist attacks and defense budget, 146 in Afghanistan, view on Islam and terrorism, 141–142 Joint short-run Granger causality, 362 Joint Task 271 Joint and exercises, 144–145 Joint Research of European Commission, Joint Task Force 333 approach, 25 riots (2016), 254 346 conflict, 146 Control of 224 for mechanism, 38 full-employment conditions, 40 55 Commission 272 policy, 309 90, 143, 149, 387 America 335 squares 241 terrorism, 404 345–346 and test test), and 77 326 77 72 of of terrorism in, 77 trade policy, effect of, 7 of 332, terrorist events in, 97 politics, 128, 132–133 rate 358 indicators of association , 403 associations among variables, 216–219 effects, 238 elasticity of FDI, 242–243 Granger causality, 362 207 328 regions, 100 regions, 100 factors, 357 impacts of terrorist activities, 50 data and methodology, empirical results, from developed countries, from developing economies, 56 literature survey, variables, 297 344 Madrid train bombing (1988), 226 Control of Crime Act of Act 391 Islamic group, 194, 236 cryptocurrency in, 131 terrorism, 90–91 defense budget, 282 attacks, conflict, 311, SHGs violence 312 in and 404 100 354 134 economies, 28 240 ideology, 76 Eigenvalue test, 288 estimation 26, 256 Organisation, 133 riots 253 cryptocurrency in, 131 and countries, 156, 187 economies, 160–162 76 terrorism, 76 expenditure, association between terrorism and, 30 distribution, 65 relationship between terrorism and, 280 terrorism and and terrorism incidence in India, 281–282 Challenge 87 129–130 of 145 Terrorism economy, 402 346 398 327 329 India’s of 141 132–133 126 126, 131 and 117 laundering 132–133 133 cryptocurrency and terror financing, of cryptocurrency for drug dealing, 133 exercises, 136–137 111, 131 102 328 120 on the of approach 156, 160 model, 158 133 Joint Task Force 268 Boko Haram and, 271–273 data and methodology, 268–269 France and, impact, policy to good results, analysis, terror attack 6, 404 143 404 Commission Act, 271 of 358 Counter Terrorism Authority 220 Counterterrorism Authority Act 220 Democratic of 387 407 effects of policy on, Agency 220 Agency Act 380 Act 393 402 387 estimation model, 358 model, 299 253 128 335 New and Agencies, New terrorist attacks in, 75, 85 237 354 Commission, 270 Nigeria, 194, 354 Boko Haram, 194, 298–299 causality relationships, 196–197 cryptocurrency in, 131 data and methodology, economic consequences of terrorism, 297–298 empirical and growth effects of terrorism, 300 foreign policy, GTI, response 197–198 measures terrorism in, 336 policy, policy, results, stability test, terrorism impact on economic growth, terrorism in, terrorist events in, 97 theoretical framework, 355 women and terrorism 335 Nigeria Civil War 271 236 76 254 9/11 attacks, 6, 140–141, 144, 224, 385 See also Al-Qaeda 402 money services, 111 regimes, 343 comparative study between democratic and, 80–81 of 336 group, 140 policy, SHGs progress of, 113–114, 118 134 participation 336 organizations, 76 public healthcare sector, equilibrium condition 15 Organization 92 West 186 Northeast India, 345 democracy in, 345–346 in political political of India riots (2017), 254 for 186 control of reservoirs, 114 terrorist attacks, 182 terrorist attacks, 28 ledger, 129 79–80 90, 92 90 25–26, squares 256 Organization for Economic and Development 89 attacks in, 144 cryptocurrency in, 131 terrorism and impact on human loss in, terrorist events in, 97 suicide tests, 250 data model, 296 analysis, unit root tests, 272 of functions, 40 SHG progress of, 311–318 of terrorism, 120 defense system, 144 111 and 272 test,

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,218
Score d'incertitude au seuil0,000

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0060,009
Études des sciences et des technologies0,0020,001
Communication savante0,0140,008
Science ouverte0,0030,005
Intégrité de la recherche0,0030,003
Charge utile insuffisante (le modèle a refusé de juger)0,7820,820

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,025
Tête enseignante GPT0,346
Écart entre enseignants0,321 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

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Publié2019
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