Pular para o conteúdo

Tarefa crb_papers.q074

crb_papersagentT2publicépoca 1, tentativa 1Execução: 20261015T171027Z-suite-crb_papers-naive-54c3f2

Veredito

passouPassou em todas as verificações obrigatórias.

Família do método (das chamadas de ferramentas): ols (regression)

Pergunta feita ao analista

What is the causal effect of municipal civil service reform adoption on the share of blue-collar municipal government jobs held by native-born white workers, estimated for municipalities whose adoption was externally induced (local compliers)?

Resposta

Estimativa ingênua (infer.ols): coef.treat_actual = -0,000000000000000004437.

Valores esperados e de onde vêm

crb_papers.q074.gold

Fonte
CausalReasoningBenchmark, causal_queries.json, index 74 (revision edd0fe1c1d1c)
Tipo
benchmark_gold
Localização
causal_queries.json['74'].effect and .standard_error
Trecho
index 74: effect -0.168896, standard_error 0.098381
Valor como publicado
-0.16889570857702552
Erro-padrão como publicado
0.09838104012319736
Valor
-0,168896-0.16889570857702552 (se 0,0983810.09838104012319736)
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: -0,168896-0.16889570857702552 · relativa 0.000001 · absoluta 9.838104012319735e-8
  • #3 figura da resposta próxima: 0,0983810.09838104012319736 · relativa 0.000001 · absoluta 9.838104012319735e-8

crb_papers.q074.script

Fonte
CausalReasoningBenchmark reference estimation script for index 74
Tipo
software
Localização
solutions/research_papers/IV/Kuipers2022/question/estimation.py
Valor
—
Conferido por
arquivo do benchmark · sha256 of the script's 591 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
21c133a31b59ed07fbd06a9a87e7c4efe65cc45c4938fe5b8c85abd5f5dc76e3 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/solutions/research_papers/IV/Kuipers2022/question/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
    -4.437399802e-18 in [-0.3617225472, 0.02393113006]?
    obrigatóriapassou[-0.36172254721849234,0.02393113006444131]-0,0000000000000000044374-4.437399801659122e-18interval · [-0.36172254721849234, 0.02393113006444131]—call_9916e16b
    2figura da resposta próxima
    -4.437399802e-18 vs -0.16889570857702552
    registradafalhou-0,168896-0.16889570857702552-0,0000000000000000044374-4.437399801659122e-18relativa 0.000001 · absoluta 9.838104012319735e-8crb_papers.q074.goldcall_9916e16b
    3figura da resposta próxima
    0.003288414081 vs 0.09838104012319736
    registradafalhou0,0983810.098381040123197360,003288410.0032884140813934522relativa 0.000001 · absoluta 9.838104012319735e-8crb_papers.q074.goldcall_9916e16b

    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.iv_2slsChamada do agente: infer.ols (call_9916e16b)diferente
    Argumentos da referência e do agente
    ArgumentoReferênciaAgente
    cluster——não fixado pela referência
    controls—[]não fixado pela referência
    dataset"ref_iv""ds_0044"diferente
    endog["treat_actual"]—ausente
    exog["pop","YEAR_1860.0","YEAR_1870.0","YEAR_1880.0","YEAR_1900.0","YEAR_1910.0","YEAR_1920.0","YEAR_1930.0","YEAR_1940.0","city_albany, ny","city_alexandria, la","city_allentown, pa","city_alliance, oh","city_altoona, pa","city_ames, ia","city_amsterdam, ny","city_anniston, al","city_appleton, wi","city_arnold, pa","city_ashland, oh","city_ashland, wi","city_ashtabula, oh","city_atlantic city, nj","city_attleboro, ma","city_auburn, ny","city_augusta, ga","city_barberton, oh","city_batavia, ny","city_baton rouge, la","city_beacon, ny","city_beaver falls, pa","city_bellaire, oh","city_beloit, wi","city_benton harbor, mi","city_bethlehem, pa","city_beverly, ma","city_binghamton, ny","city_boise, id","city_boone, ia","city_boston, ma","city_bradford, pa","city_brainerd, mn","city_brockton, ma","city_bucyrus, oh","city_buffalo, ny","city_burlington, ia","city_butler, pa","city_cambridge, ma","city_cambridge, oh","city_camden, nj","city_campbell, oh","city_canton, oh","city_carbondale, pa","city_casper, wy","city_cedar rapids, ia","city_chelsea, ma","city_chester, pa","city_cheyenne, wy","city_chicopee, ma","city_chillicothe, oh","city_cincinnati, oh","city_cleveland heights, oh","city_cleveland, oh","city_clifton, nj","city_clinton, ia","city_coatesville, pa","city_coffeyville, ks","city_cohoes, ny","city_columbia, sc","city_columbus, oh","city_connellsville, pa","city_corning, ny","city_corpus christi, tx","city_cortland, ny","city_coshocton, oh","city_council bluffs, ia","city_cudahy, wi","city_cuyahoga falls, oh","city_dallas, tx","city_davenport, ia","city_dayton, oh","city_dearborn, mi","city_denver, co","city_des moines, ia","city_dover, nj","city_du bois, pa","city_dubuque, ia","city_dunkirk, ny","city_duquesne, pa","city_east cleveland, oh","city_east liverpool, oh","city_east orange, nj","city_easton, pa","city_eau claire, wi","city_el paso, tx","city_elizabeth, nj","city_elmira, ny","city_elyria, oh","city_endicott, ny","city_erie, pa","city_euclid, oh","city_eugene, or","city_everett, ma","city_fall river, ma","city_farrell, pa","city_findlay, oh","city_fitchburg, ma","city_floral park, ny","city_fond du lac, wi","city_fort dodge, ia","city_fort madison, ia","city_fort smith, ar","city_fostoria, oh","city_franklin, pa","city_freeport, ny","city_fremont, oh","city_fulton, ny","city_gadsden, al","city_gardner, ma","city_garfield heights, oh","city_gary, in","city_geneva, ny","city_glen cove, ny","city_glens falls, ny","city_gloucester, ma","city_gloversville, ny","city_greeley, co","city_green bay, wi","city_greensburg, pa","city_greenville, sc","city_hamilton, oh","city_harrisburg, pa","city_hastings, ne","city_haverhill, ma","city_hazleton, pa","city_hempstead, ny","city_hibbing, mn","city_holyoke, ma","city_hornell, ny","city_houston, tx","city_hudson, ny","city_hutchinson, ks","city_ilion, ny","city_indianapolis, in","city_iowa city, ia","city_ironton, oh","city_irvington, nj","city_ithaca, ny","city_jackson, mi","city_janesville, wi","city_jeannette, pa","city_jersey city, nj","city_johnson city, ny","city_johnstown, ny","city_johnstown, pa","city_kansas city, ks","city_kearny, nj","city_kenmore, ny","city_kenosha, wi","city_keokuk, ia","city_kingston, ny","city_klamath falls, or","city_la crosse, wi","city_lackawanna, ny","city_lafayette, la","city_lake charles, la","city_lakewood, oh","city_lancaster, oh","city_lancaster, pa","city_lawrence, ma","city_lebanon, pa","city_leominster, ma","city_lima, oh","city_little falls, ny","city_little rock, ar","city_lockport, ny","city_lorain, oh","city_lowell, ma","city_lynbrook, ny","city_lynn, ma","city_madison, wi","city_malden, ma","city_mamaroneck, ny","city_manitowoc, wi","city_mankato, mn","city_mansfield, oh","city_marietta, oh","city_marinette, wi","city_marion, oh","city_marlborough, ma","city_marshalltown, ia","city_martins ferry, oh","city_mason city, ia","city_massillon, oh","city_mckeesport, pa","city_meadville, pa","city_medford, ma","city_melrose, ma","city_middletown, ny","city_middletown, oh","city_milwaukee, wi","city_monroe, la","city_morristown, nj","city_muscatine, ia","city_nanticoke, pa","city_new bedford, ma","city_new castle, pa","city_new philadelphia, oh","city_new rochelle, ny","city_new york, ny","city_newark, nj","city_newark, oh","city_newburgh, ny","city_newburyport, ma","city_newton, ia","city_newton, ma","city_niagara falls, ny","city_niles, oh","city_north adams, ma","city_north little rock, ar","city_north tonawanda, ny","city_northampton, ma","city_norwood, oh","city_nutley, nj","city_ogdensburg, ny","city_oil city, pa","city_olean, ny","city_omaha, ne","city_oneida, ny","city_oneonta, ny","city_orange, nj","city_orlando, fl","city_oshkosh, wi","city_oskaloosa, ia","city_ossining, ny","city_oswego, ny","city_ottumwa, ia","city_painesville, oh","city_parma, oh","city_parsons, ks","city_paterson, nj","city_peabody, ma","city_peekskill, ny","city_philadelphia, pa","city_pine bluff, ar","city_piqua, oh","city_pittsburgh, pa","city_pittsfield, ma","city_pittston, pa","city_plattsburg, ny","city_pocatello, id","city_port chester, ny","city_port huron, mi","city_port jervis, ny","city_portland, or","city_portsmouth, oh","city_pottsville, pa","city_poughkeepsie, ny","city_quincy, ma","city_racine, wi","city_rahway, nj","city_reading, pa","city_revere, ma","city_rochester, mn","city_rochester, ny","city_rome, ny","city_rutherford, nj","city_salem, ma","city_salem, oh","city_salem, or","city_salt lake city, ut","city_san antonio, tx","city_sandusky, oh","city_saratoga springs, ny","city_scranton, pa","city_shaker heights, oh","city_sharon, pa","city_sheboygan, wi","city_shorewood, wi","city_shreveport, la","city_sioux city, ia","city_somerville, ma","city_south milwaukee, wi","city_south orange, nj","city_spartanburg, sc","city_springfield, ma","city_springfield, oh","city_st. augustine, fl","city_st. cloud, mn","city_steubenville, oh","city_stevens point, wi","city_struthers, oh","city_sunbury, pa","city_superior, wi","city_syracuse, ny","city_taunton, ma","city_teaneck, nj","city_tiffin, oh","city_toledo, oh","city_tonawanda, ny","city_topeka, ks","city_trenton, nj","city_troy, ny","city_tuscaloosa, al","city_two rivers, wi","city_union, nj","city_uniontown, pa","city_utica, ny","city_waco, tx","city_waltham, ma","city_warren, oh","city_washington, pa","city_waterloo, ia","city_watertown, ny","city_watertown, wi","city_watervliet, ny","city_waukesha, wi","city_wausau, wi","city_wauwatosa, wi","city_west allis, wi","city_west orange, nj","city_westfield, ma","city_white plains, ny","city_williamsport, pa","city_woburn, ma","city_wooster, oh","city_worcester, ma","city_xenia, oh","city_yonkers, ny","city_york, pa","city_youngstown, oh","city_zanesville, oh"]—ausente
    fe—[]não fixado pela referência
    instruments["treat_assign"]—ausente
    intercept—truenão fixado pela referência
    level—0,950.95não fixado pela referência
    se"HC1""HC1"igual
    subset——não fixado pela referência
    weights——não fixado pela referência
    x—["treat_actual"]não fixado pela referência
    y"govt""govt"igual

    Pendências do caminho de referência: needs_op:iv_se_hc0

    Trajetória

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

    1. 0Início

      What is the causal effect of municipal civil service reform adoption on the share of blue-collar municipal government jobs held by native-born white workers, estimated for municipalities whose adoption was externally induced (local compliers)?

      ds_0044 (agent)

      | Variable Name | Description | |----------------|---------------------------------------------------------------------------------------------| | Unnamed/Index | Row identifier / index column carried over from the source CSV (sequence number). | | city | Municipality name and state (lowercase string, e.g., "akron, oh"). | | YEAR | Census year (decennial year) for the observation (numeric). | | occ | Occupation class for municipal employment (e.g., "blue_collar", "white_collar", "police"). | | name | Demographic group label combining race and nativity (e.g., "white_x_native_born"). | | govt | Proportion (share) of municipal government jobs in this city–year–occupation held by group. | | pop | Proportion (share) of the municipality's total population comprised by the named group. | | treat_assign | Binary indicator whether a statewide legislative mandate applied to the municipality that decade (0/1). | | treat_actual | Binary indicator whether the municipality had the municipal civil service commission in effect that decade (0/1). | | bandwidth | Numeric distance in residents between the municipality's population and the state cutoff used in assignment rules. | Data Description: This dataset is a municipality-by-decade panel that links full-count U.S. decennial census records (1850–1940) on municipal employment and population composition with administrative indicators derived from state statutes and municipal surveys. Each observation identifies a city and census year, an occupation class, and a demographic group, and reports group shares in the municipal population and in the local government workforce; the file also includes binary flags recording whether a state-level mandate applied and whether a municipal civil service commission was in place, plus a numeric distance-from-cutoff measure used for threshold-based comparisons. The underlying sources include full-count census enumerations (industry/occupation and birthplace fields), historical surveys of municipal civil service adoption, and compiled state session-law information assembled to create a harmonized longitudinal dataset on municipal staff composition.

      file d5035ee26421d944dd396fa22c1f412e72a32f59388ef130ad486a3c851a813b · frame —
      ref_iv (reference)
      file d5035ee26421d944dd396fa22c1f412e72a32f59388ef130ad486a3c851a813b · frame —
      1. filter {"query":"occ == 'blue_collar' and name == 'white_x_native_born'"}
      2. select {"columns":["govt","treat_actual","treat_assign","pop","YEAR","city"]}
      3. dropna {"columns":["govt","treat_actual","treat_assign","pop","YEAR","city"]}
      4. dummies {"column":"YEAR","drop_first":true,"prefix":"YEAR"}
      5. dummies {"column":"city","drop_first":true,"prefix":"city"}
    2. 1Turno do modelo
      call_3412d274naive-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_0044",
          "x": [
            "treat_actual"
          ],
          "y": "govt"
        }
    3. 2Ferramenta
      infer.olsv0.1.0call_9916e16bdecidido pelo modeloreexecutável

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

      Argumentos
      {
        "cluster": null,
        "controls": [],
        "dataset": "ds_0044",
        "fe": [],
        "intercept": true,
        "level": 0.95,
        "se": "HC1",
        "subset": null,
        "weights": null,
        "x": [
          "treat_actual"
        ],
        "y": "govt"
      }
      Figuras call_9916e16b
      ChaveValorValor brutoErro-padrãoIC
      coef.treat_actual
      Coefficient on treat_actual in the regression of govt
      -0,0000000000000000044374 -4.437399801659122e-180,003288410.0032884140813934522-0,00644537 – 0,00644537
      Diagnósticos
      • n_obs = 40.45240452
      • k = 22
      • r2 = -0,000000000000000444089-4.440892098500626e-16
      • df_resid = 40.45040450
      • se_type = "HC1"
      • n_clusters = —
      Tabelas (1)
      {
        "coefficients": [
          {
            "ci_high": 0.17148471419874692,
            "ci_low": 0.1618486191345864,
            "coef": 0.16666666666666666,
            "p": 0,
            "se": 0.0024581591305653325,
            "t": 67.8014147230315,
            "term": "Intercept"
          },
          {
            "ci_high": 0.006445366027085428,
            "ci_low": -0.0064453660270854364,
            "coef": -4.437399801659122e-18,
            "p": 0.9999999999999989,
            "se": 0.0032884140813934522,
            "t": -1.3494042087846772e-15,
            "term": "treat_actual"
          }
        ]
      }
      Digests dos dados
      ds_0044 70ec9feb2c796cfd98963f1948c8a52286056dadf4df3fc19d3c7179994c358f
      sha256 do resultado
      c79119b063fb1979c28c5cb9a3a8b6e54a526c736e5561ccdc9087dfd6a1345e
    4. 3Turno do modelo
      call_114b18a1naive-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.treat_actual = -0,000000000000000004437.",
          "caveats": [],
          "figure_refs": [
            "call_9916e16b:coef.treat_actual"
          ]
        }
    5. 4Guarda
      resposta aceita
      Números encontrados
      -0,000000000000000004437
      Sem lastro
      —
      Não citados
      —
      1 nova(s) tentativa(s) restante(s)
    6. 5Resposta

      Estimativa ingênua (infer.ols): coef.treat_actual = -0,000000000000000004437.

      Figuras citadas: call_9916e16b:coef.treat_actual · Parada: answered
      Figura da resposta: call_9916e16b:coef.treat_actual = -0,0000000000000000044374-4.437399801659122e-18 (se 0,003288410.0032884140813934522)
    7. 6Pontuação
      #0resposta com lastropassouobrigatóriaevery number backed
    8. 7Pontuação
      #1figura da resposta próximapassouobrigatória-4.437399802e-18 in [-0.3617225472, 0.02393113006]?
    9. 8Pontuação
      #2figura da resposta próximafalhouregistrada-4.437399802e-18 vs -0.16889570857702552
    10. 9Pontuação
      #3figura da resposta próximafalhouregistrada0.003288414081 vs 0.09838104012319736

    Épocas × verificações

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

    Tentativas

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

    Downloads desta tarefa

    Pacote da tarefa (.zip)
    104,8 KB · sha256 dc106e9b8ddced2dad488a1d38bb2c8aabd92e4889d406cade6b09c0c1e9569f

    O 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.

    Downloads desta tarefa
    ArquivoTamanhosha256
    attachments/3cd6d0361e36ea0ca3ad9caef752058bb923038e1baab70b1b2b0e4a21e23709.json268 B3cd6d0361e36ea0ca3ad9caef752058bb923038e1baab70b1b2b0e4a21e23709
    attachments/433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420.json2,4 KB433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420
    attachments/52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b.json64,0 KB52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b
    attachments/635cc40309a778d14ef5fdb51141958066eb19c6a589867016052e314f559a22.json1007 B635cc40309a778d14ef5fdb51141958066eb19c6a589867016052e314f559a22
    attachments/718d2d6153478ebfd697df629a7ae015bfc31edda752b15169b07922721c0fa1.json229 B718d2d6153478ebfd697df629a7ae015bfc31edda752b15169b07922721c0fa1
    attachments/b8cc5f573355ab714d2aaeac916ed255964cdc6a5a1d6995ddacbea63b178b6d.json2,8 KBb8cc5f573355ab714d2aaeac916ed255964cdc6a5a1d6995ddacbea63b178b6d
    attachments/f100c7292f841ea254b53e70ff7ecd5704abe89cc6438d9768da7c505a34a688.json901 Bf100c7292f841ea254b53e70ff7ecd5704abe89cc6438d9768da7c505a34a688
    native/crb_papers/crb_papers.q074.e1.a1.json4,1 KB539b6cef3216692083a4e733e55bd17f0384f43c603ad00fd7d8ffec7a372c3e
    sources/crb_papers.q074.gold.json1,1 KB00d2e9a718250a9b32b755e7ca6688623b5aebd744128a326df42fecd4822f1e
    sources/crb_papers.q074.script.json1,1 KB0a9553d97fcdb029cd8406b02dbf462b402e1a60b61ad3217230acba4abab018
    specs/crb_papers.q074.json22,2 KBc34219b8aa9595071fae1232f2af4919c9aaf06dc623116c1e56d21fd5ce22fc
    traces/crb_papers.q074.e1.a1.jsonl13,7 KBa2f677a5acadb68ed66ffca9f80d36cc18450ccc7816ed721494e2fa5a1d7a5a
    trajectories/crb_papers.q074.e1.a1.jsonl12,8 KBed5b3565a856f41631b56949f72c041f11713a325b13b1c2c6532a4c5354cc12