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update mpref texts, correct sampling of sections
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BeritJanssen committed Nov 20, 2023
1 parent 8ada095 commit e0852a2
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14 changes: 10 additions & 4 deletions backend/experiment/rules/musical_preferences.py
Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,7 @@ class MusicalPreferences(Base):
preference_offset = 20
knowledge_offset = 42
round_increment = 1
contact_email = 'musicexp_china@163.com'

know_score = {
'yes': 2,
Expand All @@ -48,7 +49,7 @@ def first_round(self, experiment):
rendered = render_to_string('consent/{}'.format(self.consent_file)
)
consent = Consent(
text=rendered, title=_('Informed consent'), confirm=_('I agree'), deny=_('Stop')
text=rendered, title=_('Informed consent'), confirm=_('I consent and continue.'), deny=_('I do not consent.')
)
playlist = Playlist(experiment.playlists.all())
explainer = Explainer(
Expand Down Expand Up @@ -182,11 +183,11 @@ def next_round(self, session, request_session=None):
session,
top_participant,
known_songs,
n_songs,
n_songs-1,
top_all
)]

section = session.playlist.random_section()
section = session.section_from_unused_song()
like_key = 'like_song'
likert = LikertQuestionIcon(
question=_('2. How much do you like this song?'),
Expand Down Expand Up @@ -232,7 +233,7 @@ def social_media_info(self, experiment, top_participant, known_songs, n_songs, t
)
format_songs = lambda songs: ', '.join([song['name'] for song in songs])
return {
'apps': ['facebook', 'twitter'],
'apps': ['weibo', 'share'],
'message': _("I explored musical preferences on %(url)s! My top 3 favorite songs: %(top_participant)s. I know %(known_songs)i out of %(n_songs)i songs. All players' top 3 songs: %(top_all)s") % {
'url': current_url,
'top_participant': format_songs(top_participant),
Expand Down Expand Up @@ -262,6 +263,11 @@ def get_final_view(self, session, top_participant, known_songs, n_songs, top_all
social=social_info
)
return view

def feedback_info(self):
info = super().feedback_info()
info['header'] = _("Any remarks or questions (optional):")
return info

def get_preferred_songs(self, result_set, n=5):
top_songs = result_set.values('section').annotate(
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Original file line number Diff line number Diff line change
Expand Up @@ -2,61 +2,62 @@
<p>{% translate "Dear participant," %}</p>
<p>
{% blocktranslate %}
You will be taking part in the Musical Preferences research project conducted by Xuan Huang under the supervision of Prof. Henkjan Honing and Dr. John Ashley Burgoyne of the Music Cognition Group at the University of Amsterdam’s Institute for Logic, Language, and Computation.
You will be taking part in the Musical Preferences research project conducted by Xuan Huang under the supervision of Prof. Henkjan Honing and Dr. John Ashley Burgoyne of the Music Cognition Group at the University of Amsterdam’s Institute for Logic, Language, and Computation.
{% endblocktranslate %}
</p>

<h4>{% translate "Purpose of the research project" %}</h4>

<p>
{% blocktranslate %}
Studies have shown that cultural preferences and familiarity for music start in infancy and continue throughout adolescence and adulthood. People tend to prefer music from their own cultural traditions. This research will help us understand individual and situational influences on musical preferences and investigate the factors that underly musical preferences in China. For example, do people who have preferences for classical music also have preferences for Chinese traditional music? Are there cultural-specific or universal structural features for musical preferences?
Studies have shown that cultural preferences and familiarity for music start in infancy and continue throughout adolescence and adulthood. People tend to prefer music from their own cultural traditions. This research will help us understand individual and situational influences on musical preferences and investigate the factors that underly musical preferences in China. For example, do people who have preferences for classical music also have preferences for Chinese traditional music? Are there cultural-specific or universal structural features for musical preferences?
{% endblocktranslate %}
</p>

{% load i18n %}
<h4>{% translate "Who can take part in this research?" %}</h4>
<h4>{% translate "Who can take part?" %}</h4>

<p>
{% blocktranslate %}
Anybody with sufficiently good hearing, natural or corrected, to enjoy music listening is welcome to participate in this research. Your device must be able to play audio, and you must have a sufficiently strong data connection to be able to stream short MP3 files. Headphones are recommended for the best results, but you may also use either internal or external loudspeakers. You should adjust the volume of your device so that it is comfortable for you.
{% endblocktranslate %}
<ol>
<li>{% translate "Legally competent participants aged 16 or older." %}</li>
<li>{% translate "Anybody with sufficient good hearing, natural or corrected, to enjoy music listening is welcome to participate in this research." %}</li>
</ol>
</p>

<h4>{% translate "Instructions" %}</h4>
<p>
{% blocktranslate %}
This study is a music preference experiment in which you will hear 64 music clips throughout the experiment, you either wear headphones or use your device's speakers to listen to the clips. Adjust the volume level of your device before the experiment begins.
This study is a music preference experiment in which you will hear 64 music clips throughout the experiment, you either wear headphones or use your device's speakers to listen to the clips. Adjust the volume level of your device before the experiment begins.
{% endblocktranslate %}
</p>

<p>
{% blocktranslate %}
The experiment has two parts. The first part is a questionnaire with 6 questions. The second part is a music preference test, where you will listen to a music clip and answer questions about it. The results of your music preferences will be available after the experiment is completed.
The experiment has two parts. The first part is a questionnaire with 6 questions. The second part is a music preference test, where you will listen to a music clip and answer questions about it. The results of your music preferences will be available after the experiment is completed.
{% endblocktranslate %}
</p>

<h4>{% translate "Voluntary participation" %}</h4>
<h4>{% translate "Voluntary participation & risks" %}</h4>

<p>
{% blocktranslate %}
You will be participating in this research project on a voluntary basis. This means you are free to stop taking part at any stage without consequences or penalty. If you decide to stop or withdraw your consent, all the information gathered up until then will be permanently deleted.
You will be participating in this research on a voluntary basis. This means you are free to stop taking part at any stage without consequences or penalty. If you decide to stop or withdraw your consent, all the information gathered up until then will be permanently deleted. This research has no known risks.
{% endblocktranslate %}
</p>

<h4>{% translate "Confidential treatment of your details" %}</h4>
<h4>{% translate "Privacy" %}</h4>

<p>
{% blocktranslate %}
The information gathered over the course of this research will be used for further analysis and publication in scientific journals only. Fully anonymised data collected during the experiment may be made available online in tandem with these scientific publications. We guarantee that you will remain anonymous under all circumstances. Your personal details will not be viewed by third parties without your express permission.
The information gathered will be used for publication in scientific journals only. Fully anonymized data may be available online in tandem with these scientific publications. We guarantee that you will remain anonymous under all circumstances. Your personal information will not be viewed by third parties without your express permission.
{% endblocktranslate %}
</p>

{% load i18n %}
<h4>{% translate "Further Information" %}</h4>

<p>
{% blocktranslate %} For further information, please contact Xuan Huang (x.huang@uva.nl) or Dr. John Ashley Burgoyne (j.a.burgoyne@uva.nl). If you have any complaints regarding this project, you can contact the Secretary of the Ethics Committee of the Faculty of Humanities of the University of Amsterdam (commissie-ethiek-fgw@uva.nl).
{% blocktranslate %} For further information, please contact Xuan Huang (x.huang@uva.nl) or Dr. John Ashley Burgoyne (j.a.burgoyne@uva.nl). If you have any complaints regarding this project, you can contact the Secretary of the Ethics Committee of the Faculty of Humanities of the University of Amsterdam (commissie-ethiek-fgw@uva.nl).
{% endblocktranslate %}
</p>

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20 changes: 0 additions & 20 deletions backend/experiment/templates/final/musical_preferences.html

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