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Linglib.Data.Experiments.ClausWalch2024

ClausWalch2024: experimental results (generated) #

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Three web-based experiments in German on how numeral modification bears on framing effects. Each offers a risky-choice framing scenario (a war zone with 600 lives at stake and a sure and a risky response plan, after Mandel 2014; participants choose a plan) or an attribute framing scenario (a project team asking for more funding after 50 projects, after Duchon et al. 1989; participants approve or reject), with the sure outcome or the team's record stated in a positive frame (lives saved, successful projects) or a negative one (lives lost, unsuccessful projects). Experiment 1 modifies the numerals with genau 'exactly', frame within subjects, both scenarios. Experiments 2 (risky choice) and 3 (attribute) cross frame, within subjects, with the modifier of the critical numeral, bis zu 'up to' or höchstens 'at most', between subjects. The tables print the share of sure-option choices or of approvals per cell; the generalized linear mixed models are reported in the text.

References #

How the outcome is stated.

  • positive : Frame

    Positive: as lives saved or successful projects

  • negative : Frame

    Negative: as lives lost or unsuccessful projects

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    def ClausWalch2024.instReprFrame.repr :
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      The upper-bounding modifier of the critical numeral in Experiments 2 and 3.

      • bisZu : Modifier

        Bis zu 'up to': the directional modifier bis zu

      • hoechstens : Modifier

        Höchstens 'at most': the superlative modifier höchstens

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          The experiment, by scenario.

          • exp1RiskyChoice : Experiment

            Experiment 1, risky-choice framing: genau, the risky-choice scenario

          • exp1Attribute : Experiment

            Experiment 1, attribute framing: genau, the attribute framing scenario

          • exp2 : Experiment

            Experiment 2: bis zu and höchstens, the risky-choice scenario

          • exp3 : Experiment

            Experiment 3: bis zu and höchstens, the attribute framing scenario

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              A fixed effect of the mixed model, with deviation coding (+.5, -.5).

              • frame : Effect

                FRAME: the main effect of frame

              • modifier : Effect

                MODIFIER: the main effect of modifier

              • interaction : Effect

                MODIFIER x FRAME: the interaction of modifier and frame

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                def ClausWalch2024.instReprEffect.repr :
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                  How a p-value is printed.

                  • below : Bound

                    <: as an upper bound

                  • exact : Bound

                    =: as a value

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                    def ClausWalch2024.instReprBound.repr :
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                      The lives at stake in the risky-choice scenario. (Experiment 1, Materials and (3), p. 4146; checked against the page images.)

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                        The lives the sure option saves in the positive frame. ((3), p. 4146; checked against the page images.)

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                          The lives lost under the sure option in the negative frame. ((3), p. 4146; checked against the page images.)

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                            The team's last projects in the attribute framing scenario. ((4), p. 4146; checked against the page images.)

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                              The successful projects, in the positive frame. ((4), p. 4146; checked against the page images.)

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                                The unsuccessful projects, in the negative frame. ((4), p. 4146; checked against the page images.)

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                                  The participants analysed in Experiment 1. (Experiment 1, Participants, p. 4146; checked against the page images.)

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                                    The participants analysed in Experiment 2. (Experiment 2, Participants, p. 4147; checked against the page images.)

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                                      The participants analysed in Experiment 3. (Experiment 3, Participants, p. 4148; checked against the page images.)

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                                        A row of Table 1, p. 4147: the proportion of sure-option choices in the risky-choice framing trials of Experiment 1, by frame.

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                                          def ClausWalch2024.instDecidableEqSureChoices1.decEq (x✝ x✝¹ : SureChoices1) :
                                          Decidable (x✝ = x✝¹)
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                                              The cells of Table 1, p. 4147, by frame; checked against the page images.

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                                                A row of Table 2, p. 4147: the proportion of approvals in the attribute framing trials of Experiment 1, by frame.

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                                                  def ClausWalch2024.instDecidableEqApprovals2.decEq (x✝ x✝¹ : Approvals2) :
                                                  Decidable (x✝ = x✝¹)
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                                                      The cells of Table 2, p. 4147, by frame; checked against the page images.

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                                                        A row of Table 3, p. 4148: the proportion of sure-option choices in the risky-choice framing trials of Experiment 2, by modifier and frame.

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                                                          def ClausWalch2024.instDecidableEqSureChoices3.decEq (x✝ x✝¹ : SureChoices3) :
                                                          Decidable (x✝ = x✝¹)
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                                                              The cells of Table 3, p. 4148, by modifier and frame; checked against the page images.

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                                                                A row of Table 4, p. 4148: the proportion of approvals in the attribute framing trials of Experiment 3, by modifier and frame.

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                                                                  def ClausWalch2024.instDecidableEqApprovals4.decEq (x✝ x✝¹ : Approvals4) :
                                                                  Decidable (x✝ = x✝¹)
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                                                                      The cells of Table 4, p. 4148, by modifier and frame; checked against the page images.

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                                                                        A row of Results and Discussion of Experiments 1–3, pp. 4146–4148: a fixed effect of the generalized linear mixed model (binomial logit, participants as random factor) fitted to an experiment's choices.

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                                                                          def ClausWalch2024.instDecidableEqMixedModelEffect.decEq (x✝ x✝¹ : MixedModelEffect) :
                                                                          Decidable (x✝ = x✝¹)
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                                                                              The 8 rows of Results and Discussion of Experiments 1–3, pp. 4146–4148, in the paper's order; checked against the page images.

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