Tarefa causcibench_real.q007

Veredito

Pergunta feita ao analista

Does being an immigrant make it less likely to get an interview request?

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
   vernby_can_immigrants— The data comes from a randomized field experiment designed to assess whether a candidate's background influences their likelihood of receiving a job interview or offer. Researchers submitted fictitious job applications to restaurants and cafes across Sweden at random. The applications varied in terms of country of birth, gender, citizenship status, work experience, and religious activity. A positive response was defined as a job offer, interview invitation, or follow-up inquiry, while a negative response included any other reply or no response at all. Variables: name: Name of the candidate stad: City citizen: 1 if the candidate is a Swedish citizen, 0 otherwise religious: 1 if the candidate is religious, 0 otherwise experience: 1 if the candidate has work experience, 0 otherwise poland: 1 if the candidate was born in Poland, 0 otherwise iraq: 1 if the candidate was born in Iraq, 0 otherwise somalia: 1 if the candidate was born in Somalia, 0 otherwise skilledjob: 1 if the job is high-skilled, 0 otherwise woman: 1 if the candidate is a woman, 0 otherwise invited: 1 if the candidate received an interview or a job or a follow-up response, 0 otherwise city1, city2, city3, city4, city5, city6, city7: Dummy variables for the seven cities immigrant: 1 if the candidate is an immigrant (not born in Sweden), 0 otherwise time: Proportion of the applicant's life spent living in Sweden (scaled between 0 and 1)
2. 2Chamada que gerou a resposta finalinfer.ols(Regressão linear por mínimos quadrados ordinários (MQO))citada na respostacoincide com a referência

   Ver chamada call_2300d1a6 nos detalhes

   causcibench_metadata_rule/1: ols

   Por que este é o caminho de referência: causcibench_metadata_rule/1: ols
   Argumentos principais

   controls:

   ["citizen","woman","religious","experience","skilledjob","time"]

   dataset:

   "vernby_can_immigrants"

   intercept:

   true

   level:

   0,950.95

   se:

   "HC1"

   x:

   ["immigrant"]

   y:

   "invited"

   Resultado calculado

   • coef.immigrant = -0,086117 -0.08611704628931742
     Coefficient on immigrant in the regression of invited
   Diagnósticos: n_obs = 1.4921492 (observations used) · k = 88 (parameters estimated, fixed-effect dummies included) · r2 = 0,06949650.06949647865468667 · df_resid = 1.4841484 · 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: -0,08612
   Figuras citadas: call_2300d1a6:coef.immigrant
   • ✓
     #0resposta com lastro

     every number in the answer was stated by a tool call
   • ✓
     #1figura da resposta próxima

     CauSciBench effect accuracy: |answer figure − gold| ≤ 5% of |gold|

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 being an immigrant make it less likely to get an interview request?

   vernby_can_immigrants (agent)

   The data comes from a randomized field experiment designed to assess whether a candidate's background influences their likelihood of receiving a job interview or offer. Researchers submitted fictitious job applications to restaurants and cafes across Sweden at random. The applications varied in terms of country of birth, gender, citizenship status, work experience, and religious activity. A positive response was defined as a job offer, interview invitation, or follow-up inquiry, while a negative response included any other reply or no response at all. Variables: name: Name of the candidate stad: City citizen: 1 if the candidate is a Swedish citizen, 0 otherwise religious: 1 if the candidate is religious, 0 otherwise experience: 1 if the candidate has work experience, 0 otherwise poland: 1 if the candidate was born in Poland, 0 otherwise iraq: 1 if the candidate was born in Iraq, 0 otherwise somalia: 1 if the candidate was born in Somalia, 0 otherwise skilledjob: 1 if the job is high-skilled, 0 otherwise woman: 1 if the candidate is a woman, 0 otherwise invited: 1 if the candidate received an interview or a job or a follow-up response, 0 otherwise city1, city2, city3, city4, city5, city6, city7: Dummy variables for the seven cities immigrant: 1 if the candidate is an immigrant (not born in Sweden), 0 otherwise time: Proportion of the applicant's life spent living in Sweden (scaled between 0 and 1)

   file 6b86133cb042567bcf438fed9ac968ded163b85e3608000503564ddb195541c6 · frame —
2. 1Turno do modelo
   call_ac278bc1referenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache

   Texto visível

   causcibench_metadata_rule/1: ols

   Chamadas pedidas

   • infer.ols

     {
       "controls": [
         "citizen",
         "woman",
         "religious",
         "experience",
         "skilledjob",
         "time"
       ],
       "dataset": "vernby_can_immigrants",
       "x": [
         "immigrant"
       ],
       "y": "invited"
     }

   Mensagens (formato neutro)Instruções do sistemaFerramentas oferecidas
3. 2Ferramenta
   infer.ols— Regressão linear por mínimos quadrados ordinários (MQO)v0.1.0call_2300d1a6decidido pelo modeloreexecutável

   Motivo: causcibench_metadata_rule/1: ols

   Argumentos

   {
     "cluster": null,
     "controls": [
       "citizen",
       "woman",
       "religious",
       "experience",
       "skilledjob",
       "time"
     ],
     "dataset": "vernby_can_immigrants",
     "fe": [],
     "intercept": true,
     "level": 0.95,
     "se": "HC1",
     "subset": null,
     "weights": null,
     "x": [
       "immigrant"
     ],
     "y": "invited"
   }

   Figuras call_2300d1a6

   Chave	Valor	Valor bruto	Erro-padrão	IC
   coef.immigrant Coefficient on immigrant in the regression of invited	-0,086117	-0.08611704628931742	0,03001230.030012326029052013	-0,144988 – -0,027246

   Diagnósticos

   • n_obs = 1.4921492 (observations used)
   • k = 88 (parameters estimated, fixed-effect dummies included)
   • r2 = 0,06949650.06949647865468667
   • df_resid = 1.4841484
   • se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
   • n_clusters = — (errors not clustered)

   Derivação matemática e pressupostos

   coef.immigrant

   1. Coeficiente de immigrant na regressão por mínimos quadrados ordinários de invited.→ -0,086117 (-0.08611704628931742)
   2. Erro-padrão robusto à heterocedasticidade (HC1): a raiz da variância estimada do coeficiente.ep = √V_jj→ 0,0300123 (0.030012326029052013)
   3. Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 1484 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": 0.0755214209536049,
         "ci_low": -0.08433776928369113,
         "coef": -0.004408174165043122,
         "p": 0.9138662296924795,
         "se": 0.04074789399922117,
         "t": -0.10818164406551606,
         "term": "Intercept"
       },
       {
         "ci_high": -0.02724595302209632,
         "ci_low": -0.14498813955653853,
         "coef": -0.08611704628931742,
         "p": 0.004170898305356206,
         "se": 0.030012326029052013,
         "t": -2.8693892704602733,
         "term": "immigrant"
       },
       {
         "ci_high": 0.04987784094925174,
         "ci_low": -0.016043714493829627,
         "coef": 0.016917063227711058,
         "p": 0.31420977224342733,
         "se": 0.016803316402836152,
         "t": 1.0067693080430067,
         "term": "citizen"
       },
       {
         "ci_high": 0.11251894133178282,
         "ci_low": 0.04821200940970115,
         "coef": 0.08036547537074198,
         "p": 0.000001048570614275135,
         "se": 0.01639175102467627,
         "t": 4.902799905254732,
         "term": "woman"
       },
       {
         "ci_high": 0.026543476724701934,
         "ci_low": -0.03822439814339393,
         "coef": -0.005840460709345997,
         "p": 0.7235621831826234,
         "se": 0.016509244765736727,
         "t": -0.35376910284032403,
         "term": "religious"
       },
       {
         "ci_high": 0.06657669986231174,
         "ci_low": -0.008891563226213164,
         "coef": 0.028842568318049287,
         "p": 0.13399645374607272,
         "se": 0.019236759426040768,
         "t": 1.4993465208597012,
         "term": "experience"
       },
       {
         "ci_high": 0.08440262177804539,
         "ci_low": -0.011199864025803079,
         "coef": 0.03660137887612116,
         "p": 0.13331809641533296,
         "se": 0.024368945894287408,
         "t": 1.5019680799858188,
         "term": "skilledjob"
       },
       {
         "ci_high": 1.3961064725181096,
         "ci_low": 0.7268180601095997,
         "coef": 1.0614622663138547,
         "p": 6.375446300637741e-10,
         "se": 0.17060072206825336,
         "t": 6.2219095760285725,
         "term": "time"
       }
     ]
   }

   Hashes SHA-256 e metadados de reprodução

   Digests dos dados

   vernby_can_immigrants 321ceca56d7e15f0f480ef67fa412659353c33e94500351553713de75069879c

   sha256 do resultado

   e60b3602948d19d1f31e23b9e79810139b94afdaf9da97a7a7bb75e1678e2c2b

   Resultado mostrado ao modelo
4. 3Turno do modelo
   call_40253ed9referenceFim: 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.immigrant = -0,08612.",
       "caveats": [],
       "figure_refs": [
         "call_2300d1a6:coef.immigrant"
       ]
     }

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

   Números encontrados

   -0,08612

   Sem lastro

   —

   Não citados

   —

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

   Estimativa (infer.ols): coef.immigrant = -0,08612.

   Figuras citadas: call_2300d1a6:coef.immigrant · Parada: answered

   Figura da resposta: call_2300d1a6:coef.immigrant = -0,086117-0.08611704628931742 (se 0,03001230.030012326029052013)
7. 6Pontuação
   #0resposta com lastropassouobrigatóriaevery number backed
8. 7Pontuação
   #1figura da resposta próximapassouobrigatória-0.08611704629 vs -0.087

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)

Downloads desta tarefa