https://github.com/ccp-eva/tango-cc

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
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DOI references
Found 2 DOI reference(s) in README
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Academic publication links
Links to: zenodo.org
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Academic email domains
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (12.2%) to scientific vocabulary

Last synced: 10 months ago · JSON representation

Repository

Basic Info

Host: GitHub
Owner: ccp-eva
Language: JavaScript
Default Branch: main
Size: 145 MB

Statistics

Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 1

Created over 2 years ago · Last pushed about 1 year ago

Metadata Files

Readme

TANGO-CC

Reference:

Prein, J. C., Bednarski, F. M., Dzabatou, A., Frank, M. C., Henderson, A. M. E., Kalbitz, J., Kanngiesser, P., Keafolu, D., Kymen, B., Manrique-Hernandez, M. V., Magazi, S., Mjica-Manrique, L., Ohlendorf, J., Olaoba, D., Pieters, W. R., Pope-Caldwell, S., Sen, U., Slocombe, K., Sparks, R. Z., Bohn, M. (2025). Measuring Variation in Gaze Following Across Communities, Ages, and Individuals: A Showcase of TANGO-CC (Task for Assessing iNdividual differences in Gaze understanding-Open-Cross-Cultural). Advances in Methods and Practices in Psychological Science, 8(1), 25152459241308170. https://doi.org/10.1177/25152459241308170

Description:

The TANGOCC captures individual- and community-level variation in gaze following. Minimal language demands and the web-app implementation allow fast and easy contextual adaptations to each community. Psychometric properties were asssessed by analyzing a data set from 2.5- to 11-year-old children from 17 diverse communities. We found good internal consistency across all ages and communities. Three different trial types familiarize participants with the task to locate a balloon and use an agent's gaze as a cue.

TANGO-CC Trials

Usage

Link to task: tango-cc

Structure

``` . dist <-- folder to put on tablet for (offline) data collection public data <-- folder with php scripts, where participant data will be saved logos landing pages src <-- folder containing all CSS and JavaScript for functionality css images <-- pic on intro slide + study svg js <-- all javascript functions sounds <-- all audio prompts study html & js ...some more config files

```

URL Parameters

language "lang": bem, chi, eng-in, eng-nz, eng-ni, eng-uk, eng-us, ger, hai, khw, lin, mar, sho, spa-ar, spa-me, swa, tur, bay, custom
number of trials per type "touch", fam", "test": number
background "bg": 01 - 04 (whitehouse, clayhouse, brickhouse, woodhouse)
agents "agents": f01 - f25 and m01 - m25, selection of chosen faces
subject ID "ID": alphanumeric code
webcam "webcam": true/false

Development

Development requires Node.js

Local Development

git clone git@github.com:ccp-eva/tango-cc.git
npm install
npm start

Deploy Application To A Server

git clone git@github.com:ccp-eva/tango-cc.git
npm install
npm run build
Upload the contents within the dist folder to your web hoster.

Owner

Name: Comparative Cultural Psychology
Login: ccp-eva
Kind: organization
Email: info_ccp@eva.mpg.de
Location: Leipzig, Germany

Website: https://www.eva.mpg.de/comparative-cultural-psychology/
Repositories: 20
Profile: https://github.com/ccp-eva

Official Repository of the Comparative Cultural Psychology Department of the Max Planck Institute for Evolutionary Anthropology

GitHub Events

Total

Push event: 2

Last Year

Push event: 2

Issues and Pull Requests

Last synced: about 1 year ago

All Time

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Total pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Total issue authors: 0
Total pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

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