133 Works

Research data for paper "Anticipanting causes and consequences"

Alan Garnham, Sam Hutton & Scarlett Child
Datasets etc for paper "Anticipating causes and consequences" currently under review
Abstract
Two visual world eye-tracking experiments investigate anticipatory looks to implicit causes and implicit consequences in two clause sentences with mental state verbs (Stimulus-Experiencer and Experiencer-Stimulus) in the first main clause, and and explicit cause or consequence in the second. The first experiment showed that, just as when all continuations are causes, people look early at the implicit cause, when all continuations are consequences they look...

Research data for paper "Anticipanting causes and consequences"

Alan Garnham, Sam Hutton & Scarlett Child
Datasets etc for paper "Anticipating causes and consequences" currently under review
Abstract
Two visual world eye-tracking experiments investigate anticipatory looks to implicit causes and implicit consequences in two clause sentences with mental state verbs (Stimulus-Experiencer and Experiencer-Stimulus) in the first main clause, and and explicit cause or consequence in the second. The first experiment showed that, just as when all continuations are causes, people look early at the implicit cause, when all continuations are consequences they look...

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 2 Late Effect Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:
Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 6720-10000ms from the beginning of the display of the picture)
Independent Variables
Vbias - Causal bias of the verb (note that consequentiality bias is to the other NP)Conj - "because" or "and so"
Sources of random effects
Part - participantsItem - items
DV is numerical, other variables are factors
The file includes other variables

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 2 Late Effect Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:
Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 6720-10000ms from the beginning of the display of the picture)
Independent Variables
Vbias - Causal bias of the verb (note that consequentiality bias is to the other NP)Conj - "because" or "and so"
Sources of random effects
Part - participantsItem - items
DV is numerical, other variables are factors
The file includes other variables

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 2 Early Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:
Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200-1100ms from the beginning of the conjunction, "because" or "and so")
Independent Variables
Vbias - Causal bias of the verb (note that consequentiality bias is to the other NP)Conj - "because" or "and so"
Sources of random effects
Part - participantsItem - items
DV is numerical, other variables are factors
The file includes other...

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 2 Early Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:
Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200-1100ms from the beginning of the conjunction, "because" or "and so")
Independent Variables
Vbias - Causal bias of the verb (note that consequentiality bias is to the other NP)Conj - "because" or "and so"
Sources of random effects
Part - participantsItem - items
DV is numerical, other variables are factors
The file includes other...

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 2 Very Early Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:
Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200-1400ms from the beginning of the padding phrase)
Independent Variables
Vbias - Causal bias of the verb (note that consequentiality bias is to the other NP)Conj - "because" or "and so"
Sources of random effects
Part - participantsItem - items
DV is numerical, other variables are factors
The file includes other variables

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 2 Very Early Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:
Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200-1400ms from the beginning of the padding phrase)
Independent Variables
Vbias - Causal bias of the verb (note that consequentiality bias is to the other NP)Conj - "because" or "and so"
Sources of random effects
Part - participantsItem - items
DV is numerical, other variables are factors
The file includes other variables

Analysis script for paper "Anticipating causes and consequences" currently under review - Example R Analysis for Experiment 1 Very Early Effect - Differences

Alan Garnham
commented R session for analysis of Experiment 1, very early effect data (differences)

Analysis script for paper "Anticipating causes and consequences" currently under review - Example R Analysis for Experiment 1 Very Early Effect - Differences

Alan Garnham
commented R session for analysis of Experiment 1, very early effect data (differences)

Sentences for experiments described in paper "Anticipating causes and consequences" currently under review

Alan Garnham
FirstSet - we took the 32 items used in our earlier implicit causality visual world studies and swapped any verbs that were not mental state verbs for verbs of that category. We changed the content of the sentences with the new verbs where necessary. We then constructed consequential ending for each of the sentences. The 32 resulting sentences were used in Experiment 1.
We constructed a second set of sentences (SecondSet), with both causal and consequential...

Sentences for experiments described in paper "Anticipating causes and consequences" currently under review

Alan Garnham
FirstSet - we took the 32 items used in our earlier implicit causality visual world studies and swapped any verbs that were not mental state verbs for verbs of that category. We changed the content of the sentences with the new verbs where necessary. We then constructed consequential ending for each of the sentences. The 32 resulting sentences were used in Experiment 1.
We constructed a second set of sentences (SecondSet), with both causal and consequential...

Example Images for experiment described in paper "Anticipating causes and consequences" currently under review

Alan Garnham
example images used in Experiments 1 and 2

Example Images for experiment described in paper "Anticipating causes and consequences" currently under review

Alan Garnham
example images used in Experiments 1 and 2

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 1 Late Effect Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:

Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 6720ms into display until the end of the display - 10sec after initial presentation)
Independent Variable
VBias - causal bias of verb (note that consequentiality bias is to the other NP)

Sources of random effects
Part - participantsItem - items
IV is numerical, other variables are factors
Other variables are included in the file.

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 1 Late Effect Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:

Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 6720ms into display until the end of the display - 10sec after initial presentation)
Independent Variable
VBias - causal bias of verb (note that consequentiality bias is to the other NP)

Sources of random effects
Part - participantsItem - items
IV is numerical, other variables are factors
Other variables are included in the file.

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 1 Early Effect Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:

Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1200ms from the beginning of the conjunction "and so")
Independent Variable
VBias - causal bias of verb (note that consequentiality bias is to the other NP)

Sources of random effects
Part - participantsItem - items
IV is numerical, other variables are factors
Other variables are included in the file.

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 1 Early Effect Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:

Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1200ms from the beginning of the conjunction "and so")
Independent Variable
VBias - causal bias of verb (note that consequentiality bias is to the other NP)

Sources of random effects
Part - participantsItem - items
IV is numerical, other variables are factors
Other variables are included in the file.

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 1 Very Early Effect Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:

Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1500ms after beginning of the padding phrase in the first clause)
Independent Variable
VBias - causal bias of verb (note that consequentiality bias is to the other NP)

Sources of random effects
Part - participantsItem - items
IV is numerical, other variables are factors
Other variables are included in the file.

Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 1 Very Early Effect Data with Differences

Alan Garnham
csv file for import into R as data frame
for the analysis:

Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1500ms after beginning of the padding phrase in the first clause)
Independent Variable
VBias - causal bias of verb (note that consequentiality bias is to the other NP)

Sources of random effects
Part - participantsItem - items
IV is numerical, other variables are factors
Other variables are included in the file.

Exterior view of the Nativity Church, Bethlehem, Palestine, c.1898-1946

Freja Howat-Maxted, Leila Sansour & Jacob Norris
This is a digital reproduction of an image held at the Library of Congress.
This photograph shows the exterior of the Church of Nativity in Bethlehem. The church is said to be the birthplace of Jesus Christ emphasising the religious importance of this site. The exterior viewpoint of the church exemplifies its architectural style and its status as one of the oldest surviving Christian churches in the world. This image is a cropped version of...

Jerusalem Street, Bonfils Fiches, c.1870

Freja Howat-Maxted, Leila Sansour & Jacob Norris
This is a digital reproduction of an image held in the Library of Congress.
This photograph shows a street in Jerusalem in the late 19th century. As a French photographer, Félix Bonfils captured the Middle East in the late 19th century from a Western perspective and achieved commercial success due to a European fascination with the 'East'. Photography depicting architecture was a common subject in his work.
This image exists as part of the Bonfils Fiches...

Jerusalem Street, Bonfils Fiches, c.1870

Freja Howat-Maxted, Leila Sansour & Jacob Norris
This is a digital reproduction of an image held in the Library of Congress.
This photograph shows a street in Jerusalem in the late 19th century. As a French photographer, Félix Bonfils captured the Middle East in the late 19th century from a Western perspective and achieved commercial success due to a European fascination with the 'East'. Photography depicting architecture was a common subject in his work.
This image exists as part of the Bonfils Fiches...

Church of the Nativity at night at Christmas, Bethlehem, Palestine, December 1945

Freja Howat-Maxted, Leila Sansour & Jacob Norris
This is a digital reproduction of an image held by the Library of Congress.
This image shows the exterior of the Church of Nativity in Bethlehem photographed at night at Christmas.
This image exists as part of the Nativity Church collection within the Library of Congress project of the Planet Bethlehem Archive.

Church of the Nativity at night at Christmas, Bethlehem, Palestine, December 1945

Freja Howat-Maxted, Leila Sansour & Jacob Norris
This is a digital reproduction of an image held by the Library of Congress.
This image shows the exterior of the Church of Nativity in Bethlehem photographed at night at Christmas.
This image exists as part of the Nativity Church collection within the Library of Congress project of the Planet Bethlehem Archive.

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