Tarefa crb_papers.q057

Veredito

Pergunta feita ao analista

For districts that moved from no Section 5 preclearance coverage in analysis period 1 to coverage in period 2 and remained covered in period 3, how did gaining coverage affect the representative's civil-rights support score between periods 1 and 3, relative to districts covered in all three periods?

Como o agente resolveu e como foi validado

Resumo passo a passo do que o agente executou, por que o caminho está correto e como cada verificação conferiu o resultado.

1. 1Preparação da base de dados
   ds_0030— | Variable Name | Description | | --- | --- | | party | Member’s party identification using standard congressional numeric codes (e.g., 100 = Democrat, 200 = Republican; other parties/independents use their conventional codes). Party is measured for the member serving in that Congress (two-year House term). | | correct | Civil-rights roll-call support score for the member in that Congress (two-year House term). Constructed as the proportion (0–1) of included civil-rights–related House roll calls on which the member voted in the direction coded as expanding (rather than restricting) civil rights; abstentions are treated as votes to restrict civil rights. The set of roll calls varies by Congress. | | dpres | District presidential partisanship: Democratic presidential vote share for the most recent presidential election prior to (or associated with) the Congress observation. Higher values indicate greater support for the Democratic presidential candidate (scale follows the replication file’s coding/transformation of election returns). | | percentblack | Share of the congressional district population that is Black (0–1), aligned to district boundaries within redistricting cycles using decennial census data and standard crosswalk/harmonization to congressional districts. | | competitive | Electoral competitiveness measure based on the margin of victory in the most recent presidential election in the district, multiplied by −1 so that larger values correspond to closer (more competitive) contests. Scale reflects the transformation used in the replication files. | | covered_new2 | Indicator (1/0) that the congressional district contained any geographic overlap with a jurisdiction subject to Section 5 preclearance during that Congress. Coverage is based on the list of covered states/counties/townships and subsequent changes due to statutory amendments and court actions (including “bail-in” and “bail-out”). Time-varying at the district–Congress level. | | black_legis | Indicator (1/0) that the district’s U.S. House member was Black in that Congress, based on congressional rosters/biographical sources. | | redistrict_decade | District identifier that is stable within a redistricting cycle (roughly a decade). This ID is intended to allow districts to be tracked consistently within-cycle despite renumbering or boundary changes across cycles. | | year3 | Ordered analysis-period index taking values 1 through 5. Use it with redistrict_decade to order observations within a district-cycle. The extract does not retain calendar years, Congress numbers, or a separate redistricting-cycle label; an index value must not be interpreted as a unique calendar Congress across the whole study. Periods named in the questions refer to these recorded index values. | | treatment | Inverse-coded coverage indicator: 1 means not covered by Section 5 preclearance and 0 means covered. In every row, treatment = 1 - covered_new2. Either existing column determines coverage, provided its coding is respected; gaining coverage means covered_new2 changes from 0 to 1, or treatment changes from 1 to 0. Neither column is an ever-covered flag. | Dataset Context: This file contains 902 district-period observations for 261 district-cycle identifiers, with at most five ordered analysis periods per identifier. It is an unbalanced extract: some units appear in only one period. The source analysis for this extract concerns Texas and the Deep South states of Alabama, Georgia, Louisiana, Mississippi, and South Carolina. It is not the full national panel. The parent collection covers House terms from 1959–60 through 1997–98, but this extract does not preserve the calendar Congress labels needed to date each row. Questions therefore specify windows using year3 rather than asserting calendar dates. The observational unit is a congressional district in a House term, with districts tracked inside redistricting cycles using redistrict_decade. The parent collection includes representatives who served the full Congress in single-member districts. Do not join different redistrict_decade identifiers as if their district boundaries were unchanged. Missing periods are absent observations, not zeros or evidence that a district was uncovered. Legislative behavior is summarized with a civil-rights support score. To build it, House roll-call votes were identified from policy agenda categories focused on civil rights, minority issues, and voting rights, and votes not directly pertinent to these topics were excluded. For each Congress-member pair, the score is the proportion of included roll calls on which the member voted in the direction coded as expanding civil rights, yielding a value between 0 and 1. Jurisdictional coverage under the Voting Rights Act’s Section 5 preclearance provision is mapped to congressional districts by geographic overlap. Coverage operated at the state, county, or township level and changed over time due to statutory amendments and court actions, including “bail-in” (placing additional jurisdictions under review) and “bail-out” (removing jurisdictions meeting statutory criteria). A district is flagged as covered in a given Congress if any part of it overlapped a covered jurisdiction during that period. District context draws on administrative sources. Demographic composition, including the share of the population that is Black, comes from the U.S. Census, harmonized to congressional boundaries within each redistricting cycle. Presidential election returns are used to compute district-level Democratic vote strength and a competitiveness proxy based on recent presidential margins. Member characteristics, including party codes and whether the representative is Black, come from standard congressional rosters and roll-call archives. The observed coverage histories include districts covered throughout a window, districts moving into coverage, and districts moving out of coverage. Six district-cycle units move from uncovered in period 1 to covered in period 2 and remain covered in period 3. There are no units observed in both periods 1 and 2 that remain uncovered in both. The questions identify their respective observation windows and use districts covered throughout those windows as the comparison population. These recorded histories describe the available data; they do not by themselves establish that the groups would have followed the same outcome trends.
   ref_c1
   ref_c2
   ref_c3
   ref_panel
   ref_years
2. 2Chamada que gerou a resposta finalinfer.ols(Regressão linear por mínimos quadrados ordinários (MQO))citada na resposta

   Ver chamada call_acae901a nos detalhes

   Linha de base ingênua: regressão do resultado no tratamento, sem controles.

   Por que este é o caminho de referência: smf.ols('correct ~ gained_coverage * post').fit(cov_type='cluster', groups=redistrict_decade)
   Argumentos principais

   dataset:

   "ds_0030"

   intercept:

   true

   level:

   0,950.95

   se:

   "HC1"

   x:

   ["treatment"]

   y:

   "correct"

   Resultado calculado

   • coef.treatment = -0,199455 -0.19945452682116785
     Coefficient on treatment in the regression of correct
   Diagnósticos: n_obs = 902902 (observations used) · k = 22 (parameters estimated, fixed-effect dummies included) · r2 = 0,01679350.016793471202155574 · df_resid = 900900 · se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
3. 3Conferência de lastro e resposta final

   Todos os 1 números escritos na resposta foram conferidos contra as ferramentas e o enunciado (nenhum número sem lastro).

   Números encontrados: -0,1995
   Figuras citadas: call_acae901a:coef.treatment
   • ✓
     #0resposta com lastro

     every number traced to a tool call or the question
   • ✗
     #1figura da resposta próxima

     CRB estimate_within_solution_ci: the answer figure inside the gold 95% interval effect ± 1.96·|SE| of source crb_papers.q057.gold (closed, evaluate_result.py; no --auto-rescale)
   • ✗
     #2figura da resposta próxima

     replication cell: the gold effect to rel 1e-6 (abs floor 1e-6·SE); never required
   • ✗
     #3figura da resposta próxima

     replication cell: the gold SE to rel 1e-6; never required

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

   For districts that moved from no Section 5 preclearance coverage in analysis period 1 to coverage in period 2 and remained covered in period 3, how did gaining coverage affect the representative's civil-rights support score between periods 1 and 3, relative to districts covered in all three periods?

   ds_0030 (agent)

   | Variable Name | Description | | --- | --- | | party | Member’s party identification using standard congressional numeric codes (e.g., 100 = Democrat, 200 = Republican; other parties/independents use their conventional codes). Party is measured for the member serving in that Congress (two-year House term). | | correct | Civil-rights roll-call support score for the member in that Congress (two-year House term). Constructed as the proportion (0–1) of included civil-rights–related House roll calls on which the member voted in the direction coded as expanding (rather than restricting) civil rights; abstentions are treated as votes to restrict civil rights. The set of roll calls varies by Congress. | | dpres | District presidential partisanship: Democratic presidential vote share for the most recent presidential election prior to (or associated with) the Congress observation. Higher values indicate greater support for the Democratic presidential candidate (scale follows the replication file’s coding/transformation of election returns). | | percentblack | Share of the congressional district population that is Black (0–1), aligned to district boundaries within redistricting cycles using decennial census data and standard crosswalk/harmonization to congressional districts. | | competitive | Electoral competitiveness measure based on the margin of victory in the most recent presidential election in the district, multiplied by −1 so that larger values correspond to closer (more competitive) contests. Scale reflects the transformation used in the replication files. | | covered_new2 | Indicator (1/0) that the congressional district contained any geographic overlap with a jurisdiction subject to Section 5 preclearance during that Congress. Coverage is based on the list of covered states/counties/townships and subsequent changes due to statutory amendments and court actions (including “bail-in” and “bail-out”). Time-varying at the district–Congress level. | | black_legis | Indicator (1/0) that the district’s U.S. House member was Black in that Congress, based on congressional rosters/biographical sources. | | redistrict_decade | District identifier that is stable within a redistricting cycle (roughly a decade). This ID is intended to allow districts to be tracked consistently within-cycle despite renumbering or boundary changes across cycles. | | year3 | Ordered analysis-period index taking values 1 through 5. Use it with redistrict_decade to order observations within a district-cycle. The extract does not retain calendar years, Congress numbers, or a separate redistricting-cycle label; an index value must not be interpreted as a unique calendar Congress across the whole study. Periods named in the questions refer to these recorded index values. | | treatment | Inverse-coded coverage indicator: 1 means not covered by Section 5 preclearance and 0 means covered. In every row, treatment = 1 - covered_new2. Either existing column determines coverage, provided its coding is respected; gaining coverage means covered_new2 changes from 0 to 1, or treatment changes from 1 to 0. Neither column is an ever-covered flag. | Dataset Context: This file contains 902 district-period observations for 261 district-cycle identifiers, with at most five ordered analysis periods per identifier. It is an unbalanced extract: some units appear in only one period. The source analysis for this extract concerns Texas and the Deep South states of Alabama, Georgia, Louisiana, Mississippi, and South Carolina. It is not the full national panel. The parent collection covers House terms from 1959–60 through 1997–98, but this extract does not preserve the calendar Congress labels needed to date each row. Questions therefore specify windows using year3 rather than asserting calendar dates. The observational unit is a congressional district in a House term, with districts tracked inside redistricting cycles using redistrict_decade. The parent collection includes representatives who served the full Congress in single-member districts. Do not join different redistrict_decade identifiers as if their district boundaries were unchanged. Missing periods are absent observations, not zeros or evidence that a district was uncovered. Legislative behavior is summarized with a civil-rights support score. To build it, House roll-call votes were identified from policy agenda categories focused on civil rights, minority issues, and voting rights, and votes not directly pertinent to these topics were excluded. For each Congress-member pair, the score is the proportion of included roll calls on which the member voted in the direction coded as expanding civil rights, yielding a value between 0 and 1. Jurisdictional coverage under the Voting Rights Act’s Section 5 preclearance provision is mapped to congressional districts by geographic overlap. Coverage operated at the state, county, or township level and changed over time due to statutory amendments and court actions, including “bail-in” (placing additional jurisdictions under review) and “bail-out” (removing jurisdictions meeting statutory criteria). A district is flagged as covered in a given Congress if any part of it overlapped a covered jurisdiction during that period. District context draws on administrative sources. Demographic composition, including the share of the population that is Black, comes from the U.S. Census, harmonized to congressional boundaries within each redistricting cycle. Presidential election returns are used to compute district-level Democratic vote strength and a competitiveness proxy based on recent presidential margins. Member characteristics, including party codes and whether the representative is Black, come from standard congressional rosters and roll-call archives. The observed coverage histories include districts covered throughout a window, districts moving into coverage, and districts moving out of coverage. Six district-cycle units move from uncovered in period 1 to covered in period 2 and remain covered in period 3. There are no units observed in both periods 1 and 2 that remain uncovered in both. The questions identify their respective observation windows and use districts covered throughout those windows as the comparison population. These recorded histories describe the available data; they do not by themselves establish that the groups would have followed the same outcome trends.

   file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —

   ref_c1 (reference)

   file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —

   1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
   2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
   3. filter {"query":"year3 == 1"}
   4. rename {"map":{"covered_new2":"c1"}}
   5. select {"columns":["redistrict_decade","c1"]}

   ref_c2 (reference)

   file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —

   1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
   2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
   3. filter {"query":"year3 == 2"}
   4. rename {"map":{"covered_new2":"c2"}}
   5. select {"columns":["redistrict_decade","c2"]}

   ref_c3 (reference)

   file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —

   1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
   2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
   3. filter {"query":"year3 == 3"}
   4. rename {"map":{"covered_new2":"c3"}}
   5. select {"columns":["redistrict_decade","c3"]}

   ref_panel (reference)

   file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —

   1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
   2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
   3. filter {"query":"year3 in [1, 3]"}
   4. dropna {"columns":["correct"]}
   5. merge {"how":"inner","on":["redistrict_decade"],"with":"ref_c1"}
   6. merge {"how":"inner","on":["redistrict_decade"],"with":"ref_c2"}
   7. merge {"how":"inner","on":["redistrict_decade"],"with":"ref_c3"}
   8. filter {"query":"(c1 == 0 and c2 == 1 and c3 == 1) or (c1 == 1 and c2 == 1 and c3 == 1)"}
   9. merge {"how":"inner","on":["redistrict_decade"],"with":"ref_years"}
   10. filter {"query":"nyears == 2"}
   11. derive {"args":{"cmp":"eq","column":"c1","value":0},"name":"gained_coverage","op":"indicator"}
   12. derive {"args":{"cmp":"eq","column":"year3","value":3},"name":"post","op":"indicator"}
   13. derive {"args":{"columns":["gained_coverage","post"]},"name":"gained_post","op":"interaction"}

   ref_years (reference)

   file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —

   1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
   2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
   3. filter {"query":"year3 in [1, 3]"}
   4. dropna {"columns":["correct"]}
   5. collapse {"aggs":[{"column":"correct","fn":"count","name":"n"}],"by":["redistrict_decade","year3"]}
   6. collapse {"aggs":[{"column":"n","fn":"count","name":"nyears"}],"by":["redistrict_decade"]}
2. 1Turno do modelo
   call_f3471420naive-olsFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   Linha de base ingênua: regressão do resultado no tratamento, sem controles.

   Chamadas pedidas

   • infer.ols

     {
       "dataset": "ds_0030",
       "x": [
         "treatment"
       ],
       "y": "correct"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.ols— Regressão linear por mínimos quadrados ordinários (MQO)v0.1.0call_acae901adecidido pelo modeloreexecutável

   Motivo: Linha de base ingênua: regressão do resultado no tratamento, sem controles.

   Argumentos

   {
     "cluster": null,
     "controls": [],
     "dataset": "ds_0030",
     "fe": [],
     "intercept": true,
     "level": 0.95,
     "se": "HC1",
     "subset": null,
     "weights": null,
     "x": [
       "treatment"
     ],
     "y": "correct"
   }

   Figuras call_acae901a

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.treatment Coefficient on treatment in the regression of correct	-0,199455	-0.19945452682116785	0,04097470.040974736711604585	-0,279872 – -0,119037

   Diagnósticos

   • n_obs = 902902 (observations used)
   • k = 22 (parameters estimated, fixed-effect dummies included)
   • r2 = 0,01679350.016793471202155574
   • df_resid = 900900
   • se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
   • n_clusters = — (errors not clustered)

   Derivação matemática e pressupostos

   coef.treatment

   1. Coeficiente de treatment na regressão por mínimos quadrados ordinários de correct.→ -0,199455 (-0.19945452682116785)
   2. Erro-padrão robusto à heterocedasticidade (HC1): a raiz da variância estimada do coeficiente.ep = √V_jj→ 0,0409747 (0.040974736711604585)
   3. Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 900 graus de liberdade vezes o erro-padrão.IC = β ± c · ep

   Pressupostos do estimador

   • the conditional mean of the outcome is linear in the regressors
   • errors are independent across observations; their variance may differ

   Tabelas (1)

   {
     "coefficients": [
       {
         "ci_high": 0.491562980377805,
         "ci_low": 0.44551879179834075,
         "coef": 0.46854088608807287,
         "p": 1.649613723923983e-201,
         "se": 0.01173038583153788,
         "t": 39.942495738577605,
         "term": "Intercept"
       },
       {
         "ci_high": -0.11903737212406292,
         "ci_low": -0.2798716815182728,
         "coef": -0.19945452682116785,
         "p": 0.000001332705149106206,
         "se": 0.040974736711604585,
         "t": -4.867743952206524,
         "term": "treatment"
       }
     ]
   }

   Hashes SHA-256 e metadados de reprodução

   Digests dos dados

   ds_0030 5f2712a5440223d2460f46c6985ad05214fe97217b291ef267a061965ba7d043

   sha256 do resultado

   93019fbe4821291eae29b2d6e5bc409f901921fa14271181b383af7c7f09e524

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_b21393ebnaive-olsFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Chamadas pedidas

   • submit_answer (meta-ferramenta)

     {
       "answer": "Estimativa ingênua (infer.ols): coef.treatment = -0,1995.",
       "caveats": [],
       "figure_refs": [
         "call_acae901a:coef.treatment"
       ]
     }

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

   Números encontrados

   -0,1995

   Sem lastro

   —

   Não citados

   —

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

   Estimativa ingênua (infer.ols): coef.treatment = -0,1995.

   Figuras citadas: call_acae901a:coef.treatment · Parada: answered

   Figura da resposta: call_acae901a:coef.treatment = -0,199455-0.19945452682116785 (se 0,04097470.040974736711604585)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta próximafalhouobrigatória-0.1994545268 in [0.2007862285, 0.5653158617]?
9. 8Pontuação
   #2figura da resposta próximafalhouregistrada-0.1994545268 vs 0.3830510450811192
10. 9Pontuação
    #3figura da resposta próximafalhouregistrada0.04097473671 vs 0.09299225335317234

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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