Hugging Face's logo

Datasets:
gmpj
/
philpapers-survey-2020

Tasks:
Question Answering
Other
Sub-tasks:
multiple-choice-qa
abstractive-qa
Languages:
English
Size:
n<1K
Tags:
philosophy
License:
Dataset card Files Community
Dataset Viewer
Full Screen
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    TypeError
Message:      float() argument must be a string or a number, not 'dict'
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 323, in compute
                  compute_first_rows_from_parquet_response(
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response
                  rows_index = indexer.get_rows_index(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 640, in get_rows_index
                  return RowsIndex(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 521, in __init__
                  self.parquet_index = self._init_parquet_index(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 538, in _init_parquet_index
                  response = get_previous_step_or_raise(
                File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 539, in get_previous_step_or_raise
                  raise CachedArtifactError(
              libcommon.simple_cache.CachedArtifactError: The previous step failed.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 92, in get_rows_or_raise
                  return get_rows(
                File "/src/libs/libcommon/src/libcommon/utils.py", line 183, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 69, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1393, in __iter__
                  example = _apply_feature_types_on_example(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1080, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1932, in encode_example
                  return encode_nested_example(self, example)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1250, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1250, in <dictcomp>
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1308, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 523, in encode_example
                  return float(value)
              TypeError: float() argument must be a string or a number, not 'dict'

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Dataset Card for PhilPapers Survey 2020

The PhilPapers Survey 2020 dataset contains the results of a survey conducted among professional philosophers on various philosophical topics.

This JSON file is offered as a more accessible format for analyzing the survey results and exploring philosophical trends, in addition to the published paper.

The data is published here with direct permission from PhilPapers.org, and shared exclusively for non-commercial use.

Dataset Details

Dataset Description

The PhilPapers Survey 2020 dataset is a collection of survey responses from professional philosophers on a wide range of philosophical topics, such as epistemology, metaphysics, ethics, and more. The survey was conducted by the PhilPapers website in 2020 to gather insights into the views and opinions of contemporary philosophers.

Dataset Sources

  • Paper: Bourget, D. & Chalmers, D. J., (2023) "Philosophers on Philosophy: The 2020 PhilPapers Survey", Philosophers' Imprint 23: 11. doi: https://doi.org/10.3998/phimp.2109

Uses

Direct Use

The PhilPapers Survey 2020 dataset can be used for various purposes, such as:

  • Analyzing the views and opinions of contemporary philosophers on different philosophical topics.
  • Comparing the results with previous PhilPapers surveys to identify trends and shifts in philosophical thought.
  • Conducting research on the current state of philosophy and the distribution of philosophical views among professionals.

Commercial use of the dataset is strictly prohibited.

Out-of-Scope Use

The dataset should not be used to make generalizations about the views of all philosophers, as the survey sample is limited to professional philosophers who chose to participate. The dataset also does not provide a comprehensive overview of all philosophical topics and may not capture the full diversity of philosophical perspectives.

Dataset Structure

The dataset is provided in a JSON format, with each key-value pair representing a philosophical question and the corresponding percentage of responses for each answer option. The questions cover various philosophical topics, and the answer options typically include specific philosophical positions or stances.

Dataset Creation

Curation Rationale

The PhilPapers Survey 2020 was conducted to gather up-to-date information on the views and opinions of professional philosophers across a wide range of philosophical topics. The survey results provide valuable insights into the current state of philosophy and can serve as a resource for researchers, students, and anyone interested in contemporary philosophical thought.

Data Collection and Processing

The survey data was collected through an online questionnaire administered by the PhilPapers website. Professional philosophers were invited to participate in the survey, and their responses were recorded and anonymized. The collected data was then processed and aggregated to calculate the percentage of responses for each answer option.

The survey was open to professional philosophers from 15 October 2020 to 16 November 2020. Invitations were sent to 7,685 individuals in two groups: one group from Australia, Canada, Ireland, New Zealand, the UK, and the US (6,112 philosophers), and a second group for all remaining countries (1,573 philosophers) 1,785 responses were received, yielding a response rate of 23.2%.

Who are the source data producers?

The source data producers are the professional philosophers who participated in the PhilPapers Survey 2020. The survey was open to philosophers from various backgrounds and institutions worldwide, with a focus on those with faculty positions or PhDs in philosophy.

The survey's target population primarily consists of English-publishing philosophers (defined as individuals with one or more English-language publications in the PhilPapers database).

Personal and Sensitive Information

The dataset does not contain any personal or sensitive information about the survey participants. The responses are anonymized and aggregated to protect the privacy of the individuals involved.

Bias, Risks, and Limitations

The PhilPapers Survey 2020 dataset has some limitations and potential biases to consider:

  • The survey sample is limited to professional philosophers who chose to participate, which may not be representative of all philosophers or philosophical views.
  • The selection of questions and answer options may not cover all relevant philosophical topics or perspectives.
  • The aggregated nature of the data limits the ability to perform granular analyses or draw conclusions about individual respondents.

Recommendations

Users should be aware of the limitations and potential biases of the dataset when interpreting and drawing conclusions from the survey results. The dataset should be used in conjunction with other sources and methods to gain a comprehensive understanding of philosophical views and trends.

Citation

BibTeX:

@article{bourgetchalmers2023,
  title={Philosophers on Philosophy: The 2020 PhilPapers Survey},
  author={Bourget, David and Chalmers, David J.},
  journal={Philosophers' Imprint},
  volume={23},
  number={11},
  year={2023},
  doi={10.3998/phimp.2109}
}

APA: Bourget, D. & Chalmers, D. J., (2023) "Philosophers on Philosophy: The 2020 PhilPapers Survey", Philosophers' Imprint 23: 11. doi: https://doi.org/10.3998/phimp.2109

More Information

For more information about the PhilPapers Survey 2020 and its methodology, please refer to the original paper: Bourget, D. & Chalmers, D. J., (2023) "Philosophers on Philosophy: The 2020 PhilPapers Survey", Philosophers' Imprint 23: 11. doi: https://doi.org/10.3998/phimp.2109

Alternatively, you can view the paper in your browser here, or visit the original survey page here.

Dataset Card Author

Greyson Jenkins

Dataset Contact

Email Greyson Jenkins

Downloads last month
40
Edit dataset card