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Then and now: a story of Ireland told through decades of postcards When Paul Kelly thinks about his childhood in Los Angeles Getting a job after jail: 'I know I've changed With a degree in social science, a master's in It is a tense and uneasy marriage of convenience that The education gap: Can schools beat the postcode lottery? At one Roddy Doyle knows more than most about Majella Redmond grew up in Castlebar, Co Mayo I may have been in Finland, rather than Denmark, but as I The videotapes were conducted by two researchers who were unaware of the aim of the experiment.

Once the context of the recording was set, one of the researchers instructed the children about the task. The children were told they must tell a story, freely chosen by them. The story must be about what happened at a particular moment in time, and must be false or true. So, they were asked to tell the truth or elaborate a spontaneous lie about what happened in a concrete temporal moment of their life past, present, future. Meanwhile, the other researcher took the record with the camera six videos for each child, being three with false content and three with true.

The children were pressed a bit to do so and to do it right. It has been argued that to give fixed instructions about when to lie and when not to means that the experimental study lacks of ecological validity Sweeney and Ceci, , but our aim was that the situation resembled a demand to the children to follow instructions from the authority obey to the parent in the occurrence of a legal trial for instance given the data pointing that children are very able to fabricate false reports to gain some advantage or to satisfy authority Bala et al.

These procedures resulted in 24 naturalistic and spontaneously performed videos with a maximum duration of about 1 min each.

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Thus, an individual and separated evaluation of them was additionally performed by three clinical judges with the aim of selecting the best videos in terms of general credibility, veracity and realism, speech quality and similar duration length. This resulted in 14 videos seven genuine, seven deceptive that lasted an average of 32 s with a minimum of 12 s and a maximum of 64 s SD: The minimum number of videos for a given child was two and the maximum, five.

These videos were submitted to the FaceReader analysis but unfortunately two of them could not be evaluated by the software due to technical reasons, so the final data analysis was performed on 12 videos six truths and six lies, minimum number of videos from the same child one, maximum four that were included in the test. These videos were presented in a computer to the sample of detectors, sequentially and in semi counterbalanced order. The scoring of the videos is explained in next sections. Facial expressions were analyzed using FaceReader software version 5.

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FaceReader works in three steps: 1 face finding, 2 face modeling, and 3 face classification. This tool finds a face using the Active Template Method.

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Then it creates a virtual, super-imposed 3D Active Appearance Model featuring almost unique marks of the face. In a third stage, scores for the intensity and probability of facial expressions for basic emotions are computed. In our study, this facial analysis software analyzed more than s of video recording, i.

In FaceReader you can choose from a list of four models to fit general, children, east-asian, and elderly so the appropriate model was selected Caucasian children between 3 and 10 years. Additionally, a variable that FaceReader takes into account consists in the characteristic facial expression that some people have by nature sad, angry, etc. To do so, the user must use one or more videos as calibration material, as it was done in the current study.

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This was to make sure that the calibration material contained a diverse set of images. This classification resulted in six emotional videos and six neutral videos, being half of them a lie and half of them a truth, respectively. Additionally, the 11 traits are categorized in three different groups: Type A: strange and extravagants paranoid, schizoid, and schizotype , Type B: immature histrionic, antisocial, narcissist, and both subtypes of emotional unstable disorders: impulsive and limit , and Type C: avoiding anankastic, dependent, and anxious.

The cutoff score is established at three points for every trait. Regarding the Deceit Detection Test, seven raw dependent variables were considered for the analyses: 1. False Positives, when the detectors thought that a statement was genuine but it was deceptive the detector believed in the girl but she was lying with a maximum of six.

False Negatives, the total score when detectors thought the statement was deceptive but it was not the detector did not believe in the girl but she was telling the truth with a maximum of six. Deception-Hits: we considered separately the scores of the detectors regarding the false statements, with a maximum of six, and the 5 Truth-Hits: the scores of the detectors regarding the true statements, with a maximum of six. It was also considered what was guessed according to the FaceReader analysis: 6 Emotional-Hits with a maximum of six for the guessed about videos with emotional content; and 7 Neutral-Hits with a maximum of six regarding the videos without emotional content.

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When the C index is 0, this indicates no bias in the judge. Being the signal a lie, a negative C index indicates a truth-bias and a positive one indicates a lie-bias. On the other hand, The Salamanca Questionnaire gave 14 scores: Three main scores for the main Type A, B, and C scales and 11 subscores for each of the personality disorders described above.

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Thus, differences between related variables were tested with the Wilcoxon Sign-Rank Test, gender differences were tested with the U Mann—Whitney test, and associations between variables were tested with a series of Spearman Rank correlations. The Table 1 shows a descriptive of the 12 videos recorded, with percent of each emotion, total sum of emotions and neutral expressions according the FaceReader analysis, as well as the classification of each video in Neutral or Emotional N vs. E and in True or False content T vs. F , and the Total Hits raw score and percent observed for each video. The mean percent of Hits for the three Emotional-True videos was Thus, the percent-difference of correct classification for the true videos depending on emotional expression was For the false videos -depending on emotional expression as well- was TABLE 1.