Tarefa causcibench_real.q145

Veredito

Pergunta feita ao analista

Does electing women in districts with close races empower other women to vote at the next election?

Valores esperados e de onde vêm

Verificações

Caminho de referência e caminho do agente

A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.

Trajetória

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

1. 0Início

   Does electing women in districts with close races empower other women to vote at the next election?

   broockman_do_female (agent)

   The dataset aims to study the influence of electing women officials on women's participation in subsequent elections. It uses data from US districts with close election races between men and women candidates. In the contests, candidates with more than 50% of the vote win. Variable description: Year: Election Year State: US state abbreviation Chamber: Whether the election is for the House (H) or the Senate (S) Name: Name of the candidate contesting the current election Pty: Political party (R = republican, D = democrat, IP = independent) of the female candidate Seat: Status of the contesting seat (I: incumbent, O = Open, etc.) GE_Win: Outcome of the election (Won or lost) womanwon: Binary variable indicating whether a woman won the election or not (1 = Won, 0 = Lost) femalecand_margin_of_victory: Margin of victory for the candidates (negative values if the candidate lost) fem_v_c_p_2: Margin of victory squared fem_v_c_p_3: Margin of victory cubed fem_v_c_p_4: Margin of victory raised to the fourth power femaleonballotnextyear: Share of women on the next election, i.e., women's voter turnout winXfem_v_c_p: Interaction between womanwon and femalecand_margin_of_victory winXfem_v_c_p_2: Interaction between womanwon and fem_v_c_p_2 winXfem_v_c_p_3: Interaction between womanwon and fem_v_c_p_3 winXfem_v_c_p_4: Interaction between womanwon and fem_v_c_p_4 absolute_margin: absolute margin of victory of one candidate over the other in the last election, i.e., abs(femalecand_margin_of_victory) femaleonballotnextyear: Binary variable indicating if a female is on the ballot of the next year's elections (1 = yes, 0 = no) femaleturnout_thiscycle: Fraction of females that turned out to vote in the reference election femaleturnout_nextcycle: Fraction of females that turned out to vote in the next election female_percentageofelectorate_th: Fraction of females in the voter electorate for the reference election female_percentageofelectorate_ne: Fraction of females in the voter electorate for the next election overall_voterturnout_thiscycle: Overall voter turnout in the reference election cycle overall_voterturnout_nextcycle: Overall voter turnout in the next election cycle

   file 79817fe2c223e23f2266493fa1deb84301c0cfa51da6444ae4ba7b40465cb2a8 · frame —
2. 1Turno do modelo
   call_46a5315freferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   causcibench_metadata_rule/1: rdd

   Chamadas pedidas

   • infer.ols

     {
       "controls": [
         "femalecand_margin_of_victory",
         "fem_v_c_p_2",
         "fem_v_c_p_3",
         "fem_v_c_p_4",
         "winXfem_v_c_p",
         "winXfem_v_c_p_2",
         "winXfem_v_c_p_3",
         "winXfem_v_c_p_4"
       ],
       "dataset": "broockman_do_female",
       "x": [
         "womanwon"
       ],
       "y": "femaleonballotnextyear"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.olsv0.1.0call_53a47bbfdecidido pelo modeloreexecutável

   Motivo: causcibench_metadata_rule/1: rdd

   Argumentos

   {
     "cluster": null,
     "controls": [
       "femalecand_margin_of_victory",
       "fem_v_c_p_2",
       "fem_v_c_p_3",
       "fem_v_c_p_4",
       "winXfem_v_c_p",
       "winXfem_v_c_p_2",
       "winXfem_v_c_p_3",
       "winXfem_v_c_p_4"
     ],
     "dataset": "broockman_do_female",
     "fe": [],
     "intercept": true,
     "level": 0.95,
     "se": "HC1",
     "subset": null,
     "weights": null,
     "x": [
       "womanwon"
     ],
     "y": "femaleonballotnextyear"
   }

   Figuras call_53a47bbf

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.womanwon Coefficient on womanwon in the regression of femaleonballotnextyear	0,400199	0.4001986575718106	0,04483760.044837606575893973	0,3123 – 0,488098

   Diagnósticos

   • n_obs = 5.6605660
   • k = 1010
   • r2 = 0,2856970.28569732107550905
   • df_resid = 5.6505650
   • se_type = "HC1"
   • n_clusters = —

   Tabelas (1)

   {
     "coefficients": [
       {
         "ci_high": 0.5571788365816446,
         "ci_low": 0.4113598661197051,
         "coef": 0.48426935135067484,
         "p": 3.282945956306249e-38,
         "se": 0.037191431532915674,
         "t": 13.020992507967328,
         "term": "Intercept"
       },
       {
         "ci_high": 0.4880975815899388,
         "ci_low": 0.3122997335536824,
         "coef": 0.4001986575718106,
         "p": 5.900292846184959e-19,
         "se": 0.044837606575893973,
         "t": 8.925513383378703,
         "term": "womanwon"
       },
       {
         "ci_high": 4.264400792375061,
         "ci_low": -0.5556358990778743,
         "coef": 1.8543824466485932,
         "p": 0.13150492239962058,
         "se": 1.2293603776547264,
         "t": 1.5084124072602967,
         "term": "femalecand_margin_of_victory"
       },
       {
         "ci_high": 26.20678511811412,
         "ci_low": -19.83861316237634,
         "coef": 3.184085977868888,
         "p": 0.7863047412222585,
         "se": 11.743974546862383,
         "t": 0.2711250748341902,
         "term": "fem_v_c_p_2"
       },
       {
         "ci_high": 70.53667552984152,
         "ci_low": -86.9500585310872,
         "coef": -8.206691500622835,
         "p": 0.8381165414964167,
         "se": 40.16731889283446,
         "t": -0.20431265334184018,
         "term": "fem_v_c_p_3"
       },
       {
         "ci_high": 68.53011659338463,
         "ci_low": -103.5893337405972,
         "coef": -17.529608573606282,
         "p": 0.6896777148794544,
         "se": 43.89942359557533,
         "t": -0.3993129553385095,
         "term": "fem_v_c_p_4"
       },
       {
         "ci_high": 0.6927112237942246,
         "ci_low": -5.093093925613422,
         "coef": -2.2001913509095985,
         "p": 0.13602620857790568,
         "se": 1.4756816304168785,
         "t": -1.4909661444305211,
         "term": "winXfem_v_c_p"
       },
       {
         "ci_high": 23.28834196871875,
         "ci_low": -31.29684277943129,
         "coef": -4.004250405356269,
         "p": 0.7736489457148079,
         "se": 13.922064837251455,
         "t": -0.28761900279634117,
         "term": "winXfem_v_c_p_2"
       },
       {
         "ci_high": 112.114852192542,
         "ci_low": -71.36893314161185,
         "coef": 20.372959525465077,
         "p": 0.6633330178857106,
         "se": 46.797920860623115,
         "t": 0.435338988373891,
         "term": "winXfem_v_c_p_3"
       },
       {
         "ci_high": 97.42382245647401,
         "ci_low": -99.49685025510617,
         "coef": -1.0365138993160725,
         "p": 0.983535635792117,
         "se": 50.22502691774267,
         "t": -0.02063739858245671,
         "term": "winXfem_v_c_p_4"
       }
     ]
   }

   • 237 rows were dropped because one of 'femaleonballotnextyear', 'womanwon', 'femalecand_margin_of_victory', 'fem_v_c_p_2', 'fem_v_c_p_3', 'fem_v_c_p_4', 'winXfem_v_c_p', 'winXfem_v_c_p_2', 'winXfem_v_c_p_3', 'winXfem_v_c_p_4' was missing

   Digests dos dados

   broockman_do_female 950d0458bf6c4207813a05b15376261911c645df01034cf394a37843c48c7f1c

   sha256 do resultado

   408dd4109450f62d2e5b81b38b9f2e5223846a8a3f9c7a411d27d7a7a051f509

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_289a79d2referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Chamadas pedidas

   • submit_answer (meta-ferramenta)

     {
       "answer": "Estimativa (infer.ols): coef.womanwon = 0,4002.",
       "caveats": [],
       "figure_refs": [
         "call_53a47bbf:coef.womanwon"
       ]
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
5. 4Guarda
   resposta aceita

   Números encontrados

   0,4002

   Sem lastro

   —

   Não citados

   —

   1 nova(s) tentativa(s) restante(s)
6. 5Resposta

   Estimativa (infer.ols): coef.womanwon = 0,4002.

   Figuras citadas: call_53a47bbf:coef.womanwon · Parada: answered

   Figura da resposta: call_53a47bbf:coef.womanwon = 0,4001990.4001986575718106 (se 0,04483760.044837606575893973)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta próximafalhouobrigatória0.4001986576 vs 0.431

Épocas × verificações

Tentativas

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

• época 1, tentativa 1falhoupontuada(exibindo)

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