Tarefa crb_papers.q022

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Pergunta feita ao analista

By how much did the State Democracy Index change from 2010 to 2012 in states that newly gained unified Republican control in 2011 versus states that did not?

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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

   By how much did the State Democracy Index change from 2010 to 2012 in states that newly gained unified Republican control in 2011 versus states that did not?

   ds_0012 (agent)

   | Variable Name | Description | | --- | --- | | index | Sequential row identifier from the file export; included for reference and not used as a substantive measure. | | Republican | Binary indicator (0/1) for unified Republican control of state government in a given year. Equals 1 when the governorship and both legislative chambers were held by Republicans; 0 otherwise (including divided or other control). Compiled from state partisan balance data with updates from legislative tracking organizations. | | state | U.S. state name (50 states). | | year | Calendar year of observation (2000–2016). | | democracy_mcmc | Continuous State Democracy Index score for the state-year, estimated via Bayesian factor analysis (MCMC) from 51 state-level indicators of electoral rules, administrative performance, districting metrics, and related practices. The scale is approximately standardized across the panel (values can be negative or positive around zero); higher values indicate stronger electoral-democracy performance. Sources feeding the indicators include election administration data (e.g., MIT Election Lab), legislative policy compilations (e.g., NCSL), gerrymandering diagnostics, and measures of policy–opinion congruence. | Dataset Context: This file is a state–year panel that assembles administrative records, policy codings, and quantitative diagnostics to summarize how U.S. states structure and administer electoral democracy. The period 2000–2016 spans consequential developments in state election law and administration, including reforms that expanded access (e.g., early voting, online and same‑day registration, and the beginnings of automatic voter registration late in the period) and policies that increased participation costs for some voters (e.g., voter ID requirements). It also covers the 2010 redistricting cycle and subsequent evaluations of district plans using established gerrymandering metrics. During these years, federal–state relations affecting elections shifted as well, including changes to Voting Rights Act oversight after 2013, which altered how and where states implemented election-law changes. The State Democracy Index (reported here as democracy_mcmc) is constructed by combining 51 indicators into a single latent score using Bayesian factor analysis designed for mixed data types (binary, ordinal, and continuous). Indicator families include: election access rules (registration and voting modalities), administrative performance (e.g., wait times, provisional ballot handling, data completeness), post‑election audit requirements, districting fairness diagnostics (efficiency gap, partisan symmetry, declination, compactness), and measures of policy–opinion alignment. Indicator inputs draw on sources such as the MIT Election Lab’s compilations of election administration statistics, the National Conference of State Legislatures’ inventories of state election laws, quantitative assessments of district plans, and state policy–opinion datasets. Scores are standardized to facilitate comparison across states and years, with higher values reflecting stronger performance on these electoral-democracy dimensions. The unified-party-control variable is built from long‑running state partisan balance datasets and contemporary updates that track which party simultaneously held the governorship and majorities in both legislative chambers in each year. Together with state names and calendar years, these fields allow analysts to align institutional configurations with contemporaneous features of election law, administration, and districting captured in the index.

   file c41bdacd62be74293e7a28a6c5d82a460ccf5f046e080a7443363bc59ff73fb0 · frame —

   ref_panel (reference)

   file c41bdacd62be74293e7a28a6c5d82a460ccf5f046e080a7443363bc59ff73fb0 · frame —

   1. select {"columns":["Republican","state","year","democracy_mcmc"]}
   2. dropna {"columns":["state","year","Republican","democracy_mcmc"]}
   3. filter {"query":"year in [2010, 2012]"}
   4. merge {"how":"left","on":["state"],"with":"ref_switch"}
   5. merge {"how":"inner","on":["state"],"with":"ref_pre"}
   6. merge {"how":"inner","on":["state"],"with":"ref_post"}
   7. filter {"query":"r_pre == 0 and ((syear == 2011 and r_post == 1) or ((syear != syear or syear > 2012) and r_post == 0))"}
   8. derive {"args":{"cmp":"eq","column":"r_post","value":1},"name":"Tgroup","op":"indicator"}
   9. derive {"args":{"cmp":"eq","column":"year","value":2012},"name":"Post","op":"indicator"}
   10. derive {"args":{"columns":["Tgroup","Post"]},"name":"DID","op":"interaction"}

   ref_post (reference)

   file c41bdacd62be74293e7a28a6c5d82a460ccf5f046e080a7443363bc59ff73fb0 · frame —

   1. select {"columns":["Republican","state","year","democracy_mcmc"]}
   2. dropna {"columns":["state","year","Republican","democracy_mcmc"]}
   3. filter {"query":"year == 2012"}
   4. select {"columns":["state","Republican"]}
   5. rename {"map":{"Republican":"r_post"}}

   ref_pre (reference)

   file c41bdacd62be74293e7a28a6c5d82a460ccf5f046e080a7443363bc59ff73fb0 · frame —

   1. select {"columns":["Republican","state","year","democracy_mcmc"]}
   2. dropna {"columns":["state","year","Republican","democracy_mcmc"]}
   3. filter {"query":"year == 2010"}
   4. select {"columns":["state","Republican"]}
   5. rename {"map":{"Republican":"r_pre"}}

   ref_switch (reference)

   file c41bdacd62be74293e7a28a6c5d82a460ccf5f046e080a7443363bc59ff73fb0 · frame —

   1. select {"columns":["Republican","state","year","democracy_mcmc"]}
   2. dropna {"columns":["state","year","Republican","democracy_mcmc"]}
   3. derive {"args":{"by":["state"],"column":"Republican","order":["year"],"periods":1},"name":"r_prev","op":"lag"}
   4. filter {"query":"Republican == 1 and r_prev == 0"}
   5. collapse {"aggs":[{"column":"year","fn":"min","name":"syear"}],"by":["state"]}
2. 1Transformação
   ref_switch · select {"columns":["Republican","state","year","democracy_mcmc"]}

   833 → 833 linhas

   Frame antes → depois: 5bc3cfb33d70 → 5bc3cfb33d70
3. 2Transformação
   ref_switch · dropna {"columns":["state","year","Republican","democracy_mcmc"]}

   833 → 833 linhas

   Frame antes → depois: 5bc3cfb33d70 → 5bc3cfb33d70
4. 3Transformação
   ref_switch · derive {"args":{"by":["state"],"column":"Republican","order":["year"],"periods":1},"name":"r_prev","op":"lag"}

   833 → 833 linhas

   Frame antes → depois: 5bc3cfb33d70 → abbd3d6b245e
5. 4Transformação
   ref_switch · filter {"query":"Republican == 1 and r_prev == 0"}

   833 → 27 linhas

   Frame antes → depois: abbd3d6b245e → c56928f5bd8e
6. 5Transformação
   ref_switch · collapse {"aggs":[{"column":"year","fn":"min","name":"syear"}],"by":["state"]}

   27 → 24 linhas

   Frame antes → depois: c56928f5bd8e → 08613c2c5326
7. 6Transformação
   ref_pre · select {"columns":["Republican","state","year","democracy_mcmc"]}

   833 → 833 linhas

   Frame antes → depois: 5bc3cfb33d70 → 5bc3cfb33d70
8. 7Transformação
   ref_pre · dropna {"columns":["state","year","Republican","democracy_mcmc"]}

   833 → 833 linhas

   Frame antes → depois: 5bc3cfb33d70 → 5bc3cfb33d70
9. 8Transformação
   ref_pre · filter {"query":"year == 2010"}

   833 → 49 linhas

   Frame antes → depois: 5bc3cfb33d70 → cc8713520f8d
10. 9Transformação
    ref_pre · select {"columns":["state","Republican"]}

    49 → 49 linhas

    Frame antes → depois: cc8713520f8d → 381b51fea11e
11. 10Transformação
    ref_pre · rename {"map":{"Republican":"r_pre"}}

    49 → 49 linhas

    Frame antes → depois: 381b51fea11e → 10afd9252cc7
12. 11Transformação
    ref_post · select {"columns":["Republican","state","year","democracy_mcmc"]}

    833 → 833 linhas

    Frame antes → depois: 5bc3cfb33d70 → 5bc3cfb33d70
13. 12Transformação
    ref_post · dropna {"columns":["state","year","Republican","democracy_mcmc"]}

    833 → 833 linhas

    Frame antes → depois: 5bc3cfb33d70 → 5bc3cfb33d70
14. 13Transformação
    ref_post · filter {"query":"year == 2012"}

    833 → 49 linhas

    Frame antes → depois: 5bc3cfb33d70 → 8c4c9a31fcc8
15. 14Transformação
    ref_post · select {"columns":["state","Republican"]}

    49 → 49 linhas

    Frame antes → depois: 8c4c9a31fcc8 → 54dcd55007eb
16. 15Transformação
    ref_post · rename {"map":{"Republican":"r_post"}}

    49 → 49 linhas

    Frame antes → depois: 54dcd55007eb → 5a497b3523fd
17. 16Transformação
    ref_panel · select {"columns":["Republican","state","year","democracy_mcmc"]}

    833 → 833 linhas

    Frame antes → depois: 5bc3cfb33d70 → 5bc3cfb33d70
18. 17Transformação
    ref_panel · dropna {"columns":["state","year","Republican","democracy_mcmc"]}

    833 → 833 linhas

    Frame antes → depois: 5bc3cfb33d70 → 5bc3cfb33d70
19. 18Transformação
    ref_panel · filter {"query":"year in [2010, 2012]"}

    833 → 98 linhas

    Frame antes → depois: 5bc3cfb33d70 → c5e542554361
20. 19Transformação
    ref_panel · merge {"how":"left","on":["state"],"with":"ref_switch"}

    98 → 98 linhas

    Frame antes → depois: c5e542554361 → 0fba2b4d82c9
21. 20Transformação
    ref_panel · merge {"how":"inner","on":["state"],"with":"ref_pre"}

    98 → 98 linhas

    Frame antes → depois: 0fba2b4d82c9 → 59a432d52b19
22. 21Transformação
    ref_panel · merge {"how":"inner","on":["state"],"with":"ref_post"}

    98 → 98 linhas

    Frame antes → depois: 59a432d52b19 → 7621f85d11f3
23. 22Transformação
    ref_panel · filter {"query":"r_pre == 0 and ((syear == 2011 and r_post == 1) or ((syear != syear or syear > 2012) and r_post == 0))"}

    98 → 64 linhas

    Frame antes → depois: 7621f85d11f3 → 5655b2e0e589
24. 23Transformação
    ref_panel · derive {"args":{"cmp":"eq","column":"r_post","value":1},"name":"Tgroup","op":"indicator"}

    64 → 64 linhas

    Frame antes → depois: 5655b2e0e589 → 2110e4ef09ac
25. 24Transformação
    ref_panel · derive {"args":{"cmp":"eq","column":"year","value":2012},"name":"Post","op":"indicator"}

    64 → 64 linhas

    Frame antes → depois: 2110e4ef09ac → 36cefb3972eb
26. 25Transformação
    ref_panel · derive {"args":{"columns":["Tgroup","Post"]},"name":"DID","op":"interaction"}

    64 → 64 linhas

    Frame antes → depois: 36cefb3972eb → 88ade232a813
27. 26Turno do modelo
    call_a37a2c4dreferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

    Texto visível

    sm.OLS(y, add_constant([Tgroup, Post, DID])).fit(cov_type='cluster', groups=state) (CR1 errors with statsmodels' default G/(G-1)·(N-1)/(N-K) correction)

    Chamadas pedidas

    • infer.ols

      {
        "cluster": "state",
        "controls": [
          "Tgroup",
          "Post"
        ],
        "dataset": "ref_panel",
        "x": [
          "DID"
        ],
        "y": "democracy_mcmc"
      }

    Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
28. 27Ferramenta
    infer.olsv0.1.0call_f32c73ffdecidido pelo modeloreexecutável

    Motivo: sm.OLS(y, add_constant([Tgroup, Post, DID])).fit(cov_type='cluster', groups=state) (CR1 errors with statsmodels' default G/(G-1)·(N-1)/(N-K) correction)

    Argumentos

    {
      "cluster": "state",
      "controls": [
        "Tgroup",
        "Post"
      ],
      "dataset": "ref_panel",
      "fe": [],
      "intercept": true,
      "level": 0.95,
      "se": "HC1",
      "subset": null,
      "weights": null,
      "x": [
        "DID"
      ],
      "y": "democracy_mcmc"
    }

    Figuras call_f32c73ff

    Chave	Valor	Valor bruto	Erro-padrão	IC
    coef.DID Coefficient on DID in the regression of democracy_mcmc	-1,01937	-1.0193657368631845	0,374660.37466032388815806	-1,78349 – -0,255241

    Diagnósticos

    • n_obs = 6464
    • k = 44
    • r2 = 0,3046270.3046270391750081
    • df_resid = 6060
    • se_type = "cluster"
    • n_clusters = 3232

    Tabelas (1)

    {
      "coefficients": [
        {
          "ci_high": 0.6875153008936722,
          "ci_low": 0.1701043889573639,
          "coef": 0.42880984492551805,
          "p": 0.001970349607291347,
          "se": 0.12684665375717807,
          "t": 3.3805373040930715,
          "term": "Intercept"
        },
        {
          "ci_high": -0.2552409684620528,
          "ci_low": -1.7834905052643162,
          "coef": -1.0193657368631845,
          "p": 0.010583181123112288,
          "se": 0.37466032388815806,
          "t": -2.7207731159904753,
          "term": "DID"
        },
        {
          "ci_high": -0.08949964832734375,
          "ci_low": -0.9898140884707207,
          "coef": -0.5396568683990323,
          "p": 0.020365254389238953,
          "se": 0.22071794665882977,
          "t": -2.4450067453427144,
          "term": "Tgroup"
        },
        {
          "ci_high": 0.30439838049247314,
          "ci_low": -0.5178920036071435,
          "coef": -0.10674681155733515,
          "p": 0.6002134888971519,
          "se": 0.20158984133017402,
          "t": -0.5295247560738928,
          "term": "Post"
        }
      ]
    }

    Digests dos dados

    ref_panel 88ade232a813e4c8afedc89554677cec793d4ad2b4bb6e1b5ac20b3676770651

    sha256 do resultado

    ef849c784880130a91e3f915b6083c14e1bf60569c217cd242cdbb760abf7f47

    Resultado mostrado ao modelo
29. 28Turno do modelo
    call_6fd2b3a7referenceFim: 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.DID = -1,019. Reference path transcribed from the item's own estimation script.",
        "caveats": [],
        "figure_refs": [
          "call_f32c73ff:coef.DID"
        ]
      }

    Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
30. 29Guarda
    resposta aceita

    Números encontrados

    -1,019

    Sem lastro

    —

    Não citados

    —

    1 nova(s) tentativa(s) restante(s)
31. 30Resposta

    Estimativa (infer.ols): coef.DID = -1,019. Reference path transcribed from the item's own estimation script.

    Figuras citadas: call_f32c73ff:coef.DID · Parada: answered

    Figura da resposta: call_f32c73ff:coef.DID = -1,01937-1.0193657368631845 (se 0,374660.37466032388815806)
32. 31Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
33. 32Pontuação
    #1figura da resposta próximapassouobrigatória-1.019365737 in [-1.753699972, -0.285031502]?
34. 33Pontuação
    #2figura da resposta próximapassouregistrada-1.019365737 vs -1.0193657368631843
35. 34Pontuação
    #3figura da resposta próximapassouregistrada0.3746603239 vs 0.3746603238881578

Épocas × verificações

Tentativas

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

• época 1, tentativa 1passoupontuada(exibindo)

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