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Tarefa crb_papers.q053

crb_papersagentT2publicépoca 1, tentativa 1Execução: 20261015T170957Z-suite-crb_papers-baseline-dae0c1

Veredito

falhouDecidida pela verificação 1: figura da resposta próxima, nenhuma estimativa citada.
no answer figure: the answer cites no effect of an estimator call

Pergunta feita ao analista

By how much did drug-related police blotter incidents per 1,000 residents change in municipalities with outsider mayors after July 1, 2016 compared with otherwise similar municipalities led by establishment mayors?

Resposta

Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.

Valores esperados e de onde vêm

crb_papers.q053.gold

Fonte
CausalReasoningBenchmark, causal_queries.json, index 53 (revision edd0fe1c1d1c)
Tipo
benchmark_gold
Localização
causal_queries.json['53'].effect and .standard_error
Trecho
index 53: effect 0.361468, standard_error 0.178085
Valor como publicado
0.36146776953030707
Erro-padrão como publicado
0.17808457478058753
Valor
0,3614680.36146776953030707 (se 0,1780850.17808457478058753)
Conferido por
arquivo do benchmark · Read from the catalog at the pinned revision by scripts/freeze_crb_papers.py; the catalog states the value its estimation script prints.
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/causal_queries.json
Licença
MIT
  • #2 figura da resposta próxima: 0,3614680.36146776953030707 · relativa 0.000001 · absoluta 1.7808457478058751e-7
  • #3 figura da resposta próxima: 0,1780850.17808457478058753 · relativa 0.000001 · absoluta 1.7808457478058751e-7

crb_papers.q053.script

Fonte
CausalReasoningBenchmark reference estimation script for index 53
Tipo
software
Localização
solutions/research_papers/DiD/Ravanilla_2022/question_1/estimation.py
Valor
—
Conferido por
arquivo do benchmark · sha256 of the script's 1624 bytes at the pinned revision; the reference path of the item is a transcription of this script into typed transforms and tool calls (never executed here).
Implementação
independente da ferramenta
sha256 da cópia lida
0c07c13d1d3b2b5004f398c32b636f98286725f157d17b51abebd2f3716782f3 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/solutions/research_papers/DiD/Ravanilla_2022/question_1/estimation.py
Licença
MIT

    Verificações

    Cada verificação, o que esperava, o que observou e a chamada que leu
    #VerificaçãoObrigatóriaResultadoEsperadoObservadoTolerânciaFonteChamada
    0resposta com lastro
    every number backed
    obrigatóriapassou—[]———
    1figura da resposta próxima
    no answer figure: the answer cites no effect of an estimator call
    obrigatóriafalhou[0.012422002960355505,0.7105135361002586]—interval · [0.012422002960355505, 0.7105135361002586]——
    2figura da resposta próxima
    no answer figure: the answer cites no effect of an estimator call
    registradafalhou0,3614680.36146776953030707—relativa 0.000001 · absoluta 1.7808457478058751e-7crb_papers.q053.gold—
    3figura da resposta próxima
    no answer figure: the answer cites no effect of an estimator call
    registradafalhou0,1780850.17808457478058753—relativa 0.000001 · absoluta 1.7808457478058751e-7crb_papers.q053.gold—

    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 · benchmark_script

    Referência: infer.olsO agente não fez uma chamada de estimação que a resposta cite.

    Trajetória

    Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.

    1. 0Início

      By how much did drug-related police blotter incidents per 1,000 residents change in municipalities with outsider mayors after July 1, 2016 compared with otherwise similar municipalities led by establishment mayors?

      ds_0028 (agent)

      | Variable Name | Description | | --- | --- | | municipality | Text identifier for a Philippine local government unit (city/municipality), concatenated as region_province_municipality. Names align with official administrative geography used by the Philippine Statistics Authority and the Commission on Elections. | | postduterte | Period flag for the administrative change on July 1, 2016: 0 indicates observations from the months before July 1, 2016; 1 indicates observations from the months on/after that date. This creates a two-period panel for each municipality. | | drug_related_pcap | Per‑capita rate of police blotter incidents related to anti‑illegal‑drugs operations in the municipality and period, scaled per 1,000 residents. Incidents are drawn from the Philippine National Police (PNP) Bantay Krimen system and follow the PNP anti‑illegal drugs operations manual (e.g., buy‑busts, search and seizure via warrant, eradication, controlled delivery, clandestine laboratory raids, in flagrante operations). Voluntary surrenders are excluded. Counts are aggregated by municipality and normalized using official population totals. | | interaction | Post‑period outsider‑executive indicator: equals 1 if a municipality’s 2016 elected mayor is classified as a non‑establishment/outsider (independent or minor‑party) and the observation falls after July 1, 2016; 0 otherwise. Constructed from 2016 mayoral election returns and party labels that distinguish establishment (Liberal Party) from independents/minor parties. By construction, this variable is 0 in all pre‑period rows. | Dataset Context: This dataset links administrative crime records to local political context around the national administration change on July 1, 2016 in the Philippines. The core measurement of policing activity comes from the Philippine National Police’s Bantay Krimen (Crime Watch) platform, which publishes geocoded police blotter entries in near–real time as reported by municipal and city police stations and organized by provincial police offices. Within these records, drug-related incidents are tagged according to the Revised PNP Manual on Anti‑Illegal Drugs Operations and Investigation. Only events requiring active police operations are included (such as buy‑busts, searches by warrant, controlled deliveries, clandestine laboratory raids, eradication, or in‑flagrante operations); voluntary surrenders are recorded by separate agencies and are not part of this series. Incidents are aggregated to the municipality/city level and scaled per capita, allowing comparisons across differently sized localities. The time structure of the file is a simple two‑period panel: one observation per municipality before July 1, 2016 and one after. This timing captures the onset of a high‑salience national campaign against illegal drugs and the subsequent operational phases that characterized policing during the early years of the new administration (including surges and pauses communicated via national directives). Because mayors play a formal role in local police supervision—such as recommending municipal police chiefs and exercising operational oversight—information on the political profile of local executives is merged using certified 2016 mayoral election returns. Party labels at that election are used to categorize mayors as establishment (Liberal Party) versus non‑establishment/outsider (independents and minor parties), reflecting short‑term access to prevailing patronage networks at the time. In sum, the dataset provides a municipality‑by‑period view of police‑recorded drug operations aligned to an administrative break in mid‑2016, with standardized geographic identifiers, a clear temporal divider, per‑capita scaling, and a constructed indicator that flags outsider‑led municipalities in the post‑change period. It is designed to facilitate analyses of how policing activity varied across places and time under the institutional and political conditions prevailing during this transition.

      file 1930004a6c443521fb50e5b4970b189df8b7b4b761e32d8610d307ad93c85cac · frame —
      ref_panel (reference)
      file 1930004a6c443521fb50e5b4970b189df8b7b4b761e32d8610d307ad93c85cac · frame —
      1. select {"columns":["municipality","postduterte","drug_related_pcap","interaction"]}
      2. dropna {"columns":["municipality","postduterte","drug_related_pcap","interaction"]}
      3. derive {"args":{"cmp":"gt","column":"postduterte","value":0},"name":"postduterte","op":"indicator"}
      4. derive {"args":{"cmp":"gt","column":"interaction","value":0},"name":"interaction","op":"indicator"}
      5. merge {"how":"inner","on":["municipality"],"with":"ref_treat"}
      6. derive {"args":{"columns":["treated","postduterte"]},"name":"treated_post","op":"interaction"}
      ref_treat (reference)
      file 1930004a6c443521fb50e5b4970b189df8b7b4b761e32d8610d307ad93c85cac · frame —
      1. select {"columns":["municipality","postduterte","drug_related_pcap","interaction"]}
      2. dropna {"columns":["municipality","postduterte","drug_related_pcap","interaction"]}
      3. derive {"args":{"cmp":"gt","column":"postduterte","value":0},"name":"postduterte","op":"indicator"}
      4. derive {"args":{"cmp":"gt","column":"interaction","value":0},"name":"interaction","op":"indicator"}
      5. filter {"query":"postduterte == 1"}
      6. collapse {"aggs":[{"column":"interaction","fn":"max","name":"treated"}],"by":["municipality"]}
    2. 1Turno do modelo
      call_334d7154rules-1Fim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
      Chamadas pedidas
      • submit_answer (meta-ferramenta)
        {
          "answer": "Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.",
          "caveats": [],
          "figure_refs": []
        }
    3. 2Guarda
      resposta aceita
      Números encontrados
      —
      Sem lastro
      —
      Não citados
      —
      1 nova(s) tentativa(s) restante(s)
    4. 3Resposta

      Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.

      Figuras citadas: — · Parada: answered
    5. 4Pontuação
      #0resposta com lastropassouobrigatóriaevery number backed
    6. 5Pontuação
      #1figura da resposta próximafalhouobrigatóriano answer figure: the answer cites no effect of an estimator call
    7. 6Pontuação
      #2figura da resposta próximafalhouregistradano answer figure: the answer cites no effect of an estimator call
    8. 7Pontuação
      #3figura da resposta próximafalhouregistradano answer figure: the answer cites no effect of an estimator call

    Épocas × verificações

    Resultado de cada verificação em cada época pontuada
    #0123
    Época 1passoufalhoufalhoufalhou

    Tentativas

    Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.

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