DOI: 10.7910/dvn/ni3k31
title: Dataset for 'Variability in First Academic Medicine Job Offers in Pulmonary and Critical Care Medicine'

description: This dataset comprises responses to an electronic survey distributed to Pulmonary and Critical Care Medicine (PCCM) graduates (2020–2025) who accepted positions in academic medicine. The survey collected data on key components of first academic job offers, including salary, start-up package amounts and details, bonuses, non-clinical full-time equivalent (FTE) percentages, and the presence of career development awards prior to negotiation. Respondents included both physician-scientists and clinician-educators, with information received from 60 respondents for a total of 103 job offers. Demographic data (e.g., gender, training institution retention) and details regarding the number of job offers received were also captured. The dataset enables subgroup analyses comparing physician-scientists and clinician-educators, as well as assessment of associations between job offer characteristics and factors such as gender, retention at training institution, and prior career development awards. We provide the structured answers here but have removed free-text comments to best maintain respondent anonymity. This resource is intended to enhance transparency and inform future efforts to improve equity in academic job negotiations within PCCM.
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&lt;b&gt;Files:&lt;/b&gt;&lt;br&gt;
survey.pdf - front end survey appearance &lt;br&gt;
data_dictionary.csv - data dictionary and nested response logic&lt;br&gt;
dataset.csv - dataset of structured responses&lt;br&gt;
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Code from our analysis are available at: https://github.com/cag-lab/pccm_job_negotiation
description: Restricted Access Policy

Access to this dataset is governed by a restricted access policy to ensure the privacy and confidentiality of all survey respondents and to maintain the integrity of the collected data.

Applicants requesting access must submit a brief statement outlining their intended scientific research use of the dataset. Access will be granted only to individuals or research teams that demonstrate a valid and ethical scientific need that aligns with the scope and intent of the original study.

By applying for dataset access, you agree to the following terms:

<strong>Non-Identification:</strong> You will not attempt to identify or re-identify any survey respondents, directly or indirectly, using the dataset or in combination with other datasets.

<strong>Attribution and Citation:</strong> You will provide appropriate attribution and citation to the dataset and the associated publication in any presentations, reports, or manuscripts that utilize the data.

<strong>Data Security and Confidentiality:</strong> You will implement appropriate safeguards to ensure the dataset remains confidential and is not exposed to unauthorized parties.

<strong>No Redistribution:</strong> You will not share, distribute, or otherwise make the dataset available to others, including colleagues or collaborators, without explicit written permission from the dataset custodians.

<strong>Non-Commercial Use:</strong> You will not use the dataset for any commercial purposes, including product development, marketing, or any activity primarily intended for financial gain.

<strong>Compliance:</strong> You will comply with all applicable laws, institutional policies, and ethical guidelines governing the use of human subjects research data.

Failure to adhere to these terms may result in revocation of access and notification of your institution's research integrity office. The dataset custodians reserve the right to review all requests and deny access at their discretion.

To apply, please submit:

Your name, institutional affiliation, and contact information
A brief research proposal (1–2 paragraphs) describing the intended use of the dataset
Statement of agreement to the terms outlined above


Please note that all requests will be reviewed by the study team, and additional information may be requested to ensure compliance with ethical and privacy standards.