This CS_person_readme.txt file was generated on 2022-07-15 by Raquel Fernández Fuertes & Tamara Gómez Carrero
 
INDEX OF THE CS_person (Codeswitching experimental data: Grammatical person)
1. GENERAL INFORMATION 
1.1. Title of dataset 
1.2. Author information 
1.2.1. PI and co-PI
1.2.2. Lab
1.2.3. People involved in the data collection 
1.3. Objectives 
1.4. Funding sources 
1.5. Citing information 
2. ACCESS INFORMATION 
2.1. Licenses or restrictions 
2.2. Publications 
3. METHODOLOGICAL INFORMATION 
3.1. Data elicitation and participant groups
3.1.1. Offline data
3.1.2. Online data
3.2. Data codification procedure
3.3. Data extraction procedure 
3.4. Data classification procedure: variables 
3.4.1. Offline database variables
3.4.2. Online database variables 
4. DATA 
4.1. Database
4.2. Last update 
5. RELATED DATASETS 
 
1. GENERAL INFORMATION 
 
1.1. Title of dataset: CS_person_dataset
 
1.2. Author Information 
1.2.1. PI and co-PI:  
Name: Raquel Fernández Fuertes 
Institution: University of Valladolid 
Address: Facultad de Filosofía y Letras, Paseo del Cauce s/n 47011, Valladolid 
(Spain) 
Email: raquelff@uva.es 

Name: Tamara Gómez Carrero
Institution: University of Valladolid 
Address: Facultad de Filosofía y Letras, Paseo del Cauce s/n 47011, Valladolid 
(Spain) 
Email: tamara.gomez.carrero@uva.es 

1.2.2. Lab: 
            Name of the lab: UVALAL (University of Valladolid Language Acquisition Lab) 
            Institution: University of Valladolid 
            Address: https://uvalal.uva.es  
            Email: gir.uvalal@uva.es 

1.2.3. People involved in the data collection 
      The offline data were collected and codified by Esther Álvarez de la Fuente, Patricia Carro García, Raquel Fernández Fuertes, Tamara Gómez Carrero, Juliana Naleiro, Noelia Recio Fernández and Pablo Sánchez Martín. 
      The online data were collected by Esther Álvarez de la Fuente, Raquel Fernández Fuertes, Tamara Gómez Carrero and Sonja Mujcinovic.

1.3. Objectives 
  This investigation focuses on codeswitching happening between the subject and the verb. In particular, it aims at determining how English-Spanish subject-verb switches are perceived and processed by taking into account three issues: (i) the directionality of the switch (i.e., Spanish subject – English verb switches - examples b- vs. English subject – Spanish verb switches – examples a-); (ii) the categorial nature of the subject (i.e., determiner phrase -DP-1- vs. pronoun-2-); and (iii) the grammatical person in the case of the pronominal subjects (i.e., first and second person-3 and 4- vs. third person pronominal subjects-2-). 
  
(1) a) The boy bebe agua 	→ the boy-EN DP SUBJ. bebe-SP V 
      b) El niño drinks water	→ el niño-SP DP	SUBJ. drinks-EN V 
      
(2) a) He bebe agua		→ he-EN 3rd PERS. SING. SUBJ. bebe-SP V 
b) Él drinks water		→ él-SP 3rd PERS. SING. PRON. SUBJ. drinks-EN V 

(3) a) I quiero ese vestido	→ I-EN 1st PERS. SING. PRON. SUBJ. quiero-SP V 
b) Yo want a big hat		→ yo-SP 1st PERS. SING. PRON. SUBJ. want-EN V 

(4) a) You juegas a la pelota	→ you-EN 2nd PERS. SING. PRON. SUBJ. juegas-SP V
b) Tú cook everyday		→ tú-SP 2nd PERS. SING. PRON. SUBJ. cook-EN V

[Note. DP=Determiner Phrase; EN=English; PERS.=Person; PRON.=Pronoun; SING=Singular; SUBJ=Subject; SP=Spanish; V=Verb]


1.4. Funding sources 
- 2018-2022: Spanish Ministry of Science, Innovation and Universities and European Regional Development Fund (ERDF) [PGC2018-097693-B-I00], Linguistic competence indicators in heritage and non-native languages: linguistic, psycholinguistic and social aspects of English-Spanish bilingualism, PRINCIPAL INVESTIGATOR: R. Fernández Fuertes (University of Valladolid, Spain)
- 2017-2019: Regional Government of Castile and León (Spain) and ERDF [VA009P17], Aspectos de la dimensión internacional del contacto de lenguas: diagnósticos de la competencia lingüística bilingüe inglés-español, PRINCIPAL INVESTIGATOR: R. Fernández Fuertes (University of Valladolid, Spain) 
- 2010-2012: International Council for Canadian Studies & Department of Foreign Affairs and International Trade [Canada-Europe Award], Minority and majority languages in Canada and Spain: English, French and Spanish as first, second and heritage languages, PRINCIPAL INVESTIGATOR: R. Fernández Fuertes (University of Valladolid, Spain)
- 2006-2008: Regional Government of Castile and León (Spain) [VA046A06], Lenguas en contacto [inglés/español] en el contexto de Castilla y León: adquisición de L1 y L2, PRINCIPAL INVESTIGATOR: R. Fernández Fuertes (University of Valladolid, Spain)
- 2002-2005: Spanish Ministry of Science and Technology and ERDF [BFF2002-00442], La teoría lingüística y el análisis de los sistemas bilingües simultáneos del inglés y del español, PRINCIPAL INVESTIGATOR: R. Fernández Fuertes (University of Valladolid, Spain)

   1.5. Citing information 
      Publications using this dataset (or any part of it) should cite this dataset as follows: 
                
Fernández Fuertes, R., J.M. Liceras and A. Alba de la Fuente. 2016. Beyond the subject DP versus the subject pronoun divide in agreement switches. In Tortora, C., M. den Dikken, I.L. Montoya and T. O’Neill (eds.). Romance Linguistics 2013: Selected Papers from the 43rd Linguistic Symposium on Romance Languages (LSRL). John Benjamins.

2. ACCESS INFORMATION 
2.1. Licenses or restrictions: There are no licenses/restrictions placed on this data set.

2.2. Publications: A partial or total access to information contained in the database can be found at the UVALAL webpage (publications section, http://uvalal.uva.es/index.php/results/publications) 


3. METHODOLOGICAL INFORMATION 
3.1. Data elicitation
      Two types of data were collected for the present investigation. The offline data were collected at the University of Valladolid and at the International School of Valladolid (Spain); at the Bayside Comprehensive School and at the Westside School in Gibraltar (UK); and at the University of Florida (USA). 
      The online data were collected at the University of Valladolid and at the International School of Valladolid (Spain); and at the University of Gibraltar and at the John Mackintosh Hall in Gibraltar (UK). 

      3.1.1. Offline data
      
      The offline data were elicited via an acceptability judgment task in which participants were presented an image representing a scene and a dialogue (a question with an answer containing a switch between the subject and the verb). Each participant had to rate the answer to the question by choosing an emoticon face representing a value (very bad, bad, good and excellent). The task was designed in collaboration with Juana M. Liceras from the LAR-LAB of the University of Ottawa (Canada).
      This was a pen-and-paper task. Participants were tested in groups in a room where they were shown a PowerPoint presentation with the images and the dialogues. Each participant wrote down their rates on an answer sheet. If the participant was too young, the task was completed individually in oral mode with the help of the researcher. 

  In the case of the offline data, 325 participants completed the acceptability judgment task, organized into the following groups:

[Note. L1=first language or mother tongue; L2=second language; L3=third language; HL=heritage language]

- L1 Spanish – L2 English (110 adults, 49 children)
- L1 Spanish – HL English (8 adults, 32 children) 
- L1 English – HL Spanish (31 adults and 11 children from Florida; and 14 adults and 33 children from Gibraltar) 
- L1 English – L2 Spanish (8 adults, 22 children)
- L1 English – L3 Spanish (1 adult, 2 children)
- L2 English participants whose L1 was different from Spanish (2 adults, 2 children)
      
      3.1.2. Online data
      The online data were elicited via an eyetracking task which combines eyetracking during reading and judgments. Participants were asked to observe an image which gave them some visual context during 2500 ms. After that, they had to read a sentence which appeared isolated on the screen, and which was related to the previous image while their eye movements were recorded. An EyeLink Portable Duo was used which sampled eye-movements at 1000 Hz (degrees of visual angle were at 0.67 horizontally and 0.44 vertically, at 600 mm of viewing distance). Once they finished reading the sentence, they moved to the judgment screen by pressing the spacebar. They judged the sentence by clicking on an emoticon face representing a value (very bad, bad, good, excellent). Participants were tested individually in a quiet room and at least one researcher was present during the testing. The task was organized into four blocks so participants could take breaks when needed. Block 1 and block 2 correspond to part 1 of the experiment, which focuses on both the directionality of the switch and the categorial nature of the subject. Block 3 and block 4 correspond to part 2 of the experiment, which focuses on both the directionality of the switch and the grammatical person of the pronominal subject.
      
  In the case of the online data, 42 participants carried out the eyetracking during reading with judgments task. They were organized into the following groups:
- L1 Spanish – L2 English (1 adult and 24 children)
- L1 Spanish – HL English (5 children)
- L1 English – HL Spanish (12 adults from Gibraltar)
      

  3.2. Data codification procedure
	The codification of the offline data depended on the type of task. In the case of offline data, the answers were codified by using numbers from 1 to 4 (1=very bad; 2=bad; 3=good; 4=excellent).

      In the case of the eyetracking during reading task, the eyetracking measures used in the analysis of the data were selected by using the DataViewer software (SR-Research). Both the judgments given to each sentence and the fixations in each region or interest area (pre-target region, the two target regions and the post-target region) were extracted, organized, and cleaned using the DataViewer. After that, the data were transferred to an Excel document. 

  3.3. Data extraction procedure
     All the data collected and codified are compiled in the following csv files:
- CS_person_offline.csv
- CS_person_online.csv

3.4. Data classification: variables 
 
Both databases are in long format (one answer per row).
    
    3.4.1. Offline database variables: 
 
- Identifying variables: participant code; item number; list (A, B).
- Demographic variables: group; L1 (ES=Spanish; EN=English); HL (ES=Spanish; EN=English); L2; L3 (FR=French; CA=Catalan; PT=Portuguese; DA=Danish; DE=German; IT=Italian; GL=Galician; HI=Hindi; HU=Hungarian; EU=Basque; ZH=Chinese; AR=Arabic; NL=Dutch; GA=Irish; BG=Bulgarian; RO=Romanian); age of the participant (years); sex (F=Female; M=Male); place of present residence (Florida, Gibraltar, UK, Spain).

- Linguistic variables: 
- Task:
      AJT_agr = acceptability judgment task
      
- Structure:
      agr2 =experimental item
      Filler = filler item
      
- Condition:
LEDF = Spanish lexical verb, English DP subject with a feminine Spanish translation equivalent (e.g., the girl estudia mucho – “the girl studies a lot”).
LEDM = Spanish lexical verb, English DP subject with a masculine Spanish translation equivalent (e.g., the man tropieza – “the man trips”).
LEP1 = Spanish lexical verb, English first person singular pronominal subject (e.g., I tomo el sol – “I sunbathe”).
LEP2 = Spanish lexical verb, English second person singular pronominal subject (e.g., you haces gymnasia – “you exercise”).
LEP3F = Spanish lexical verb, English third person singular feminine pronominal subject (e.g., she compra el pantalón – “she buys trousers”).
LEP3M = Spanish lexical verb, English third person singular masculine pronominal subject (e.g., he viaja en el tren – “he travels by train”).
LSDF = English lexical verb, Spanish feminine DP subject (e.g., la niña breaks furniture – “the girl breaks furniture”).
LSDM = English lexical verb, Spanish masculine DP subject (e.g., el niño paints landscapes – “the boy paints landscapes”).
LSP1 = English lexical verb, Spanish first person singular pronominal subject (e.g., yo carry my umbrella – “I carry my umbrella”).
LSP2 = English lexical verb, Spanish second person singular pronominal subject (e.g., tú cook every day – “you cook everyday”).
LSP3F = English lexical verb, Spanish third person singular feminine pronominal subject (e.g., ella signs in the morning – “she signs in the morning”).
LSP3M = Spanish lexical verb, Spanish third person singular masculine pronominal subject (e.g., él talks on the phone – “he talks on the phone”).
     X = filler.

- Answer:
	1= very bad
	2= bad 
	3= good 
	4= excellent
      555 = no answer or more than one answer
      

    3.4.2. Online database variables: 
    
- Identifying variables: participant code; trial number; interest area (1=pre-target region; 2=target region; 3=post-target region); IA_label (label of the interest area: the part of the sentence each region corresponds to); target (the target region of each sentence); exp_part (experiment part; 1=first part of the experiment, blocks 1 and 2; 2=second part of the experiment, blocks 3 and 4).
- Demographic variables: group; proficiency level (beginner, intermediate, advanced); age of the participant (years); sex (F=female; M=male).
- Linguistic variables:
- Conditions:

DPEN = English DP subject, Spanish verb (experiment part 1) (e.g., in the morning the boy toma agua fría – “in the morning the boy drinks cold water”)
PronEN = English pronominal subject, Spanish verb (experiment part 1) (e.g., in the morning he toma agua fría – “in the morning he drinks cold water”)
DPSP = Spanish DP subject, English verb (experiment part 1) (e.g., por las mañanas el niño drinks cold water – “in the morning the boy drinks cold water”)
PronSP = Spanish pronominal subject, English verb (experiment part 1) (e.g., por las mañanas él drinks cold water fría – “in the morning he drinks cold water”)

1_2EN = English first/second person singular pronominal subject, Spanish verb (experiment part 2) (e.g., during my holidays I pienso en mi perro – “during my holidays I think about my dog” / for this question you sabes la respuesta – “for this question you know the answer”)
3EN = English third person singular pronominal subject, Spanish verb (experiment part 2) (e.g., during his holidays he piensa en su perro – “during his holidays he thinks about his dog”)
1_2SP = Spanish first/second person singular pronominal subject, English verb (experiment part 2) (e.g., durante las vacaciones yo think about my dog – “during my holidays I think about my dog” / para esta pregunta tú know the answer – “for this question you know the answer”)
3SP = Spanish third person singular pronominal subject, English verb (experiment part 2) (e.g., durante las vacaciones él thinks about his dog – “during my holidays he thinks about his dog”)

- Subject_person:

	DP = DP subject, third person (experiment part 1)
	Pron = pronominal subject, third person (experiment part 1)
1_2 = first / second person singular pronominal subject (experiment part 2)
	3 = third person singular pronominal subject (experiment part 2)

- Subject_type:
	DP = DP subject (experiment part 1)
     Pron = pronominal subject (experiment part 1 and part 2)

- Lang_subject:
	SP= Spanish
	EN = English

- Answer variables:
IA_first_fix_progressive: 1=no higher interest areas in earlier fixations have been fixated before the first fixation in the current interest area; 0=higher interest areas in earlier fixations have been fixated before the first fixation in the current interest area.

Regression_path: eyetracking measure in milliseconds. The duration of fixations that starts when the eye enters a target region until the eye moves to the right to exit the region. IA_first_fix_progressive must be 1.

Total_fixation_duration: eyetracking measure in milliseconds. The eyetracking measure to analyze the total amount of time on each of the interest areas. 

Judgments: judgment given to each sentence. 4 values: 1=very bad; 2=bad; 3=good; 4=excellent.
    
4. DATA 
   4.1. Database 
   
   The databases contain the raw data in long form with all the information related to the dataset. Each database is organized according to the variables described in section 3.4.
   
CS_person_offline.csv: it contains the offline data elicited via the acceptability judgment task from 325 participants organized into diverse groups according to their linguistic backgrounds. Number of variables = 15; number of rows = 11035.

CS_person_online.csv: it contains the online data elicited via the eyetracking during reading with judgments task from 42 participants organized into diverse groups according to their linguistic backgrounds. Number of variables = 18; number of rows = 5903.
   
   
   4.2. Last update: 2022


5. RELATED DATASETS
- Bilingual acquisition data: 
CS_DP_gender_dataset: https://uvadoc.uva.es/handle/10324/54598
CS_copula_dataset: https://uvadoc.uva.es/handle/10324/54597