How significant are the public dimensions of faculty work in review, promotion, and tenure documents?
- Simon Fraser University, Canada
- Arizona State University, United States
- University of Vermont, United States
- Universidad Nacional Autónoma de México, Mexico
Abstract
Much of the work done by faculty at both public and private universities has significant public dimensions: it is often paid for by public funds; it is often aimed at serving the public good; and it is often subject to public evaluation. To understand how the public dimensions of faculty work are valued, we analyzed review, promotion, and tenure documents from a representative sample of 129 universities in the US and Canada. Terms and concepts related to public and community are mentioned in a large portion of documents, but mostly in ways that relate to service, which is an undervalued aspect of academic careers. Moreover, the documents make significant mention of traditional research outputs and citation-based metrics: however, such outputs and metrics reward faculty work targeted to academics, and often disregard the public dimensions. Institutions that seek to embody their public mission could therefore work towards changing how faculty work is assessed and incentivized.
Data availability
The data that support the findings of this study are available in the Harvard Dataverse with the identifier https://doi.org/10.7910/DVN/VY4TJE (Alperin et al., 2019). These data include the list of institutions and academic units for which we have acquired documents along with an indicator of whether each term and concept studied was found in the documents for the institution or academic unit. The data also include the aggregated values and chi-square calculations reported. The code used for computing these aggregations can be found on Github https://github.com/ScholCommLab/rpt-project (Alperin, 2019). The documents collected are available on request from the corresponding author (JPA). These documents are not publicly available due to copyright restrictions.
-
Terms and Concepts found in Tenure and Promotion Guidelines from the US and CanadaHarvard Dataverse, 2018-05-22.
Article and author information
Author details
Juan Pablo Alperin
Funding
Open Society Foundations (OR2016-29841)
- Juan Pablo Alperin
- Meredith T Niles
- Erin C McKiernan
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Alperin et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,450
- views
-
- 536
- downloads
-
- 101
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
How significant are the public dimensions of faculty work in review, promotion, and tenure documents?
eLife 8:e42254.
https://doi.org/10.7554/eLife.42254
Further reading
-
- Computational and Systems Biology
Plasmid construction is central to life science research, and sequence verification is arguably its costliest step. Long-read sequencing has emerged as a competitor to Sanger sequencing, with the principal benefit that whole plasmids can be sequenced in a single run. Nevertheless, the current cost of nanopore sequencing is still prohibitive for routine sequencing during plasmid construction. We develop a computational approach termed Simple Algorithm for Very Efficient Multiplexing of Oxford Nanopore Experiments for You (SAVEMONEY) that guides researchers to mix multiple plasmids and subsequently computationally de-mixes the resultant sequences. SAVEMONEY defines optimal mixtures in a pre-survey step, and following sequencing, executes a post-analysis workflow involving sequence classification, alignment, and consensus determination. By using Bayesian analysis with prior probability of expected plasmid construction error rate, high-confidence sequences can be obtained for each plasmid in the mixture. Plasmids differing by as little as two bases can be mixed as a single sample for nanopore sequencing, and routine multiplexing of even six plasmids per 180 reads can still maintain high accuracy of consensus sequencing. SAVEMONEY should further democratize whole-plasmid sequencing by nanopore and related technologies, driving down the effective cost of whole-plasmid sequencing to lower than that of a single Sanger sequencing run.
-
- Biochemistry and Chemical Biology
- Computational and Systems Biology
Protein–protein interactions are fundamental to understanding the molecular functions and regulation of proteins. Despite the availability of extensive databases, many interactions remain uncharacterized due to the labor-intensive nature of experimental validation. In this study, we utilized the AlphaFold2 program to predict interactions among proteins localized in the nuage, a germline-specific non-membrane organelle essential for piRNA biogenesis in Drosophila. We screened 20 nuage proteins for 1:1 interactions and predicted dimer structures. Among these, five represented novel interaction candidates. Three pairs, including Spn-E_Squ, were verified by co-immunoprecipitation. Disruption of the salt bridges at the Spn-E_Squ interface confirmed their functional importance, underscoring the predictive model’s accuracy. We extended our analysis to include interactions between three representative nuage components—Vas, Squ, and Tej—and approximately 430 oogenesis-related proteins. Co-immunoprecipitation verified interactions for three pairs: Mei-W68_Squ, CSN3_Squ, and Pka-C1_Tej. Furthermore, we screened the majority of Drosophila proteins (~12,000) for potential interaction with the Piwi protein, a central player in the piRNA pathway, identifying 164 pairs as potential binding partners. This in silico approach not only efficiently identifies potential interaction partners but also significantly bridges the gap by facilitating the integration of bioinformatics and experimental biology.
