{{ block title }}
    Completion of the experiment
{{ endblock }}

{{ block content }}




    {% if is_ghost %}
        <div class="alert alert-warning">
            <h4 class="alert-heading"><i class="bi bi-exclamation-triangle"></i> Note on the course of the game</h4>
            <p>
                Due to multiple time-outs (<strong>{{ strikes }} Timeouts</strong>)
                your decisions in the last few rounds were automatically taken over by an algorithm.
            </p>
        </div>

        <p>
            Data collection for your part of the study is now complete.
        </p>


    {% else %}
        <div class="alert alert-success text-center">
            <h4 class="alert-heading"><i class="bi bi-trophy"></i> Congratulations!</h4>
            <p class="mb-0">You have successfully completed the experiment.</p>
        </div>

        <p class="mt-4">
            Thank you very much for your time and your focused participation in this experiment.
            Your data has been successfully saved and makes a valuable contribution to our research.
        </p>


    {% endif %}

    <p>
        The goal of this research was to examine how <strong> the position of early adopters</strong> (those who first try something new) and the <strong> characteristics of the network structure </strong>
        affects how quickly innovations or a new behavior spreads through a social network. For that you played a coordination game where your earnings depended on matching choices with your neighbours in the network.
    </p>

    <div class="info-card">
        <h4><i class="bi bi-diagram-3"></i> The Network</h4>
        <p>You played in a group of <strong>24 positions</strong>. To test our hypotheses, the group was composed of:</p>
        <ul class="list-group list-group-flush mb-3">
            <li class="list-group-item"><strong>18 Real Participants:</strong> Like yourself, making independent choices.</li>
            <li class="list-group-item"><strong>6 Computer-Controlled "Bots":</strong> Acting based on a predetermined algorithm described below</li>
        </ul>

        <p>
            The use of the bots allowed us to manipulate the behaviour of the specific early adopters positions throughout phase 1 and 2:
        </p>
    </div>

    <div class="row  mb-4">
        <div class="col-sm-6">
            <div class="p-3 border rounded shadow-sm h-100">
                <h5>Phase 1</h5>
                <p class="small text-muted">
                    Bots followed the majority choice of their neighbors.
                    This established a baseline behavior for the entire group.
                </p>
            </div>
        </div>
        <div class="col-sm-6">
            <div class="p-3 border rounded shadow-sm h-100">
                <h5>Phase 2</h5>
                <p class="small text-muted text-left">
                    Bots switched to the <strong>alternative option</strong> that was not established in phase 1.
                    We measured if this minority could convince the rest of the group to switch.
                </p>
            </div>
        </div>
    </div>

     <p>
         In addition we manipulated two factors across different groups: the <strong> structure of the social network </strong>  (some networks had tight clusters of connections, others had random connections) and if bots were placed in <strong>highly connected (powerful)</strong>
        positions or in random positions within the network. Our Hypotheses are that early adopters placed on powerful positions accelerates social tipping compared to a random positioning and that the effect is even stronger in a less clustered network.
     </p>

    <div class="mt-4">
        <h4>Why is this important?</h4>
        <p>
            This research helps us understand how to more effectively promote beneficial societal changes, such as adopting sustainable behaviors to address climate change.
        </p>
    </div>
    {% if is_ghost %}
        <div class="card bg-light mt-3">
            <div class="card-body">
                <strong>Next steps:</strong><br>
               <p>
                You can now <strong>close</strong> this browser tab. Thank you very much for joining us.
            </p>
            </div>
        </div>

    {% else %}
        <div class="card bg-light mt-3">
            <div class="card-body">
                <strong>Next steps:</strong><br>
                Click on the Button to go back to Prolific and collect your payment.
            </div>
        </div>

        <div class="mt-4 text-center">
            <a href="https://www.prolific.com/" class="btn btn-outline-secondary">Go to Prolific</a>
        </div>

    {% endif %}
    <p> If you have any questions, concerns or complaints about this research, its procedures, risks and benefits, contact the Protocol Director, Sara Constantino, smc77@stanford.edu </p>

{{ endblock }}