Tarefa causcibench_real.q150
causcibench_realagentT2publicépoca 1, tentativa 1Execução: 20261015T171059Z-suite-causcibench_real-scripted-ded01dVeredito
Família do método (das chamadas de ferramentas): iv (two-stage least squares)
Pergunta feita ao analista
How much does earmarked funding affect the performance of international organisations?
Estimativa (infer.iv_2sls): coef.EMST = -1,501.
Valores esperados e de onde vêm
causcibench_real.gold.q150
- Fonte
- CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 150
- Tipo
- benchmark_gold
- Localização
- real_input.json, record id 150: fields effect and std_error
- Trecho
id 150 effect -1.501 std_error 0.711
- Valor como publicado
-1.501- Erro-padrão como publicado
0.711- Valor
- -1,501
-1.501(se 0,7110.711) - Conferido por
- arquivo do benchmark · Written by scripts/freeze_causcibench_real.py from the pinned file; equal to the `answer` and `std_error` of the same id in data/metadata_csv/real_input.csv at the pin.
- sha256 da cópia lida
c1f4c8930675afff63d816d8ed066941ae92697e7bfc31e9d38519398dd80438(identifica a cópia lida, não um arquivo canônico)- Endereço
https://raw.githubusercontent.com/causalNLP/CauSciBench/d9bb43a2d90f261978cc5ac0b628c0484f6e8956/data/metadata_json/real_input.json- Licença
- CauSciBench repository (MIT for code; metadata as published in the repository)
- #1 figura da resposta próxima: -1,501
-1.501· relativa 0.05
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | resposta com lastro every number backed | obrigatória | passou | — | [] | — | — | — |
| 1 | figura da resposta próxima -1.500625817 vs -1.501 | obrigatória | passou | -1,501-1.501 | -1,50063-1.5006258173803875 | relativa 0.05 | causcibench_real.gold.q150 | call_fd8a6dff |
Caminho de referência e caminho do agente
A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.
caminho de referência do item · metadata_rule
| Argumento | Referência | Agente | |
|---|---|---|---|
| cluster | — | — | não fixado pela referência |
| dataset | "reinsberg_does_earmarked" | "reinsberg_does_earmarked" | igual |
| endog | ["EMST"] | ["EMST"] | igual |
| exog | ["newmopan"] | ["newmopan"] | igual |
| instruments | ["meanwSIM"] | ["meanwSIM"] | igual |
| level | — | 0,950.95 | não fixado pela referência |
| se | — | "HC1" | não fixado pela referência |
| subset | — | — | não fixado pela referência |
| y | "y1" | "y1" | igual |
Trajetória
Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.
- 0Início
How much does earmarked funding affect the performance of international organisations?
reinsberg_does_earmarked(agent)The dataset compiles performance evaluations of 32 international organizations (IOs) from 2009 to 2021, encompassing 64 assessments conducted by the Multilateral Organization Performance Assessment Network (MOPAN). Organizations vary significantly in their funding composition, with some receiving predominantly core contributions that provide operational flexibility, while others rely heavily on earmarked resources that restrict fund usage to specific purposes, sectors, or geographic areas. Due to their specific nature, earmarked funding does not offer flexibility. Thus, there is a possibility that earmarked funding may limit organizational performance. The dataset tracks both short-term and long-term earmarked funding patterns alongside core funding levels. International organizations' performance is given by two metrics: 1) Process performance, the extent to which organizations have rules to plan and manage operations strategically, and 2) outcome performance, which measures the organization's success in achieving desired results. Variables: organization: international organization name acronym: organization abbreviation year: assessment year mopan: The version of MOPAN methodology used in the assessment (one of 3.0, 3.1, or 3.0*, CA = older version) newmopan: Binary variable that is 1 if the new MOPAN assessment methodology was used y1: process performance factor score y2: outcome performance factor score y1n: process performance factor score after removing 2 micro indicators y2n: outcome performance factor score after removing 2 micro indicators EMST: earmarked funding share in the year before MOPAN assessment (t-1 year) EMLT: earmarked funding share in the years t-2 and t-3 before MOPAN assessment, i.e., 2 and 3 years before un: indicator for UN system organizations (1 = UN organization, 0 = non-UN organization) coreSTd: non-core funding amount coreST: core funding amount emST: earmarked funding amount emST_MBI: earmarked funding amount computed by MOPAN emshareLTd: Share of earmarked funding in the IO budget based on data from UN DESA Data emshareLTb: Share of earmarked funding in the IO budget based on data from UN Data Cube emshareLT: Share of earmarked funding share for long-term projects nproj_lt: number of earmarked projects ndon_lt: number of donors providing earmarked funding states_num: number of member states states_unga_sd: standard deviation of the preferences of the member states with respect to ideal point estimates tenure: executive head tenure length selectorate: Variable indicating how the executive is selected (1 = appointed by the chief of parent organization, 2 = selected by the board, 3 = chosen by the assembly of member states) founding: organization founding year hq: headquarters location field_presence: number of staff in the field staff_count: total staff size normio: indicator for norm-making IOs: FAO, ILO, UNESCO, UNHCR, UNIDO, WHO, GEF lnsectors: logarithm of the number of sectors in which the organization receives donor funding meanwSIM: weighted mean cosine similarity of sector-specific contribution profile, which is proportional to the total budget of the IOs
filec6e6f76a45840b38e6b9ab7ca8618731926c8df7c3c57d54ce2a34d8d362f330· frame — - 1Turno do modelo
call_c1f6af88referenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheTexto visívelcauscibench_metadata_rule/1: iv
Chamadas pedidasinfer.iv_2sls{ "dataset": "reinsberg_does_earmarked", "endog": [ "EMST" ], "exog": [ "newmopan" ], "instruments": [ "meanwSIM" ], "y": "y1" }
- 2Ferramenta
infer.iv_2slsv0.1.0call_fd8a6dffdecidido pelo modeloreexecutávelMotivo: causcibench_metadata_rule/1: iv
Argumentos
{ "cluster": null, "dataset": "reinsberg_does_earmarked", "endog": [ "EMST" ], "exog": [ "newmopan" ], "instruments": [ "meanwSIM" ], "level": 0.95, "se": "HC1", "subset": null, "y": "y1" }Figuras call_fd8a6dff Chave Valor Valor bruto Erro-padrão IC coef.EMST 2SLS effect of EMST on y1-1,50063 -1.50062581738038750,735008 0.7350075466238339-2,98291 – -0,0183418 Diagnósticosfirst_stage_F.EMST= 45,07545.0750057061979partial_r2.EMST= 0,4312510.43125062503238787weak_instrument=falsen_obs= 4646se_type="HC1"n_clusters= —
Tabelas (3)
{ "coefficients": [ { "ci_high": 1.7259268750794408, "ci_low": -0.25536808244781384, "coef": 0.7352793963158135, "p": 0.1417419170822108, "se": 0.49122393548353027, "t": 1.496831369978033, "term": "Intercept" }, { "ci_high": 0.6005805514870955, "ci_low": -0.6485575733162326, "coef": -0.023988510914568537, "p": 0.9386190515919255, "se": 0.30969974626807545, "t": -0.07745731536313281, "term": "newmopan" }, { "ci_high": -0.018341831730520397, "ci_low": -2.9829098030302545, "coef": -1.5006258173803875, "p": 0.04735217727016545, "se": 0.7350075466238339, "t": -2.0416468161086594, "term": "EMST" } ], "first_stage": [ { "ci_high": 1.6398794295321455, "ci_low": 0.8822738026406576, "coef": 1.2610766160864015, "endog": "EMST", "instrument": "meanwSIM", "p": 3.346539847734253e-8, "se": 0.18783372772046456, "t": 6.713792200105534 } ], "reduced_form": [ { "ci_high": -0.07147623558318639, "ci_low": -3.713332020004712, "coef": -1.8924041277939492, "instrument": "meanwSIM", "p": 0.04201790139442328, "se": 0.9029280189153219, "t": -2.095852701599929 } ] }- 18 rows were dropped because one of 'y1', 'EMST', 'meanwSIM', 'newmopan' was missing
- Digests dos dados
reinsberg_does_earmarked5e2cf774bc4e473b2623db2b5c2e832456bd6da928a073ef89f69de82001d0be- sha256 do resultado
ebe4840797c42a7342022b654647bec9eea2175cdfbc0201ec98606cee604133
- 3Turno do modelo
call_10af753breferenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheChamadas pedidassubmit_answer(meta-ferramenta){ "answer": "Estimativa (infer.iv_2sls): coef.EMST = -1,501.", "caveats": [], "figure_refs": [ "call_fd8a6dff:coef.EMST" ] }
- 4Guardaresposta aceita
- Números encontrados
- -1,501
- Sem lastro
- —
- Não citados
- —
1 nova(s) tentativa(s) restante(s) - 5Resposta
Estimativa (infer.iv_2sls): coef.EMST = -1,501.
Figuras citadas:call_fd8a6dff:coef.EMST· Parada:answeredFigura da resposta:call_fd8a6dff:coef.EMST= -1,50063-1.5006258173803875(se 0,7350080.7350075466238339) - 6Pontuação#0resposta com lastropassouobrigatória
every number backed - 7Pontuação#1figura da resposta próximapassouobrigatória
-1.500625817 vs -1.501
Épocas × verificações
| # | 0 | 1 |
|---|---|---|
| Época 1 | passou | passou |
Tentativas
Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.
- época 1, tentativa 1passoupontuada(exibindo)
Downloads desta tarefa
bd72f574a23fa4eaf098425661b5023dae0b963a84354304d6a5c9365bcf1c39O hash de um zip é só de transporte: o que ancora a integridade é o RUN_SHA256SUMS que vai dentro dele, cópia exata do SHA256SUMS da execução.
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|---|---|---|
| attachments/31999b306e56265882598ade057f22d7ac6ecd1f519e6825ac00bd5512fd96c2.json | 1,5 KB | 31999b306e56265882598ade057f22d7ac6ecd1f519e6825ac00bd5512fd96c2 |
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| attachments/433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420.json | 2,4 KB | 433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420 |
| attachments/4aac48349396b62bcf7c8e1fa85e072eb9f17dfedd94740f4ce8ab3f0fc67a66.json | 237 B | 4aac48349396b62bcf7c8e1fa85e072eb9f17dfedd94740f4ce8ab3f0fc67a66 |
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| native/causcibench_real/causcibench_real.q150.e1.a1.json | 1,7 KB | fbccc6d51c2eb2bd0c4550b5ae4484e345cc33e90f163357ca71ae2a0ad3627c |
| sources/causcibench_real.gold.q150.json | 1,2 KB | 4159d8efd01a7c4c3ee4c9859a4b3f3f343ae3880d2aa3b1b813576dfdebfb61 |
| specs/causcibench_real.q150.json | 7,0 KB | 2f99073863d349754f552179d57a358119c8ac3f02ba36d09353ad724a5581e0 |
| traces/causcibench_real.q150.e1.a1.jsonl | 16,0 KB | a2d28ff4ba93916baeb7ebf984b778549a8634a544a61e69573be8705655494d |
| trajectories/causcibench_real.q150.e1.a1.jsonl | 12,6 KB | 1dc4ba4e77c2127f73c5652553781bfb44bc99b8ee9760edd071acdbaac5ab1d |