In OpenSym 2017, we made several changes to the way the conference has been run:
* In previous years, OpenSym had tracks on topics like free/open source software, wikis, open innovation, open education, and so on. In 2017, **we used a single track model**.
-* Because we eliminated tracks, we also eliminated track-level chairs. Instead, **we appointed a series of Associate Chairs or ACs**.
+* Because we eliminated tracks, we also eliminated track-level chairs. Instead, **we appointed Associate Chairs or ACs**.
* **We eliminated page limits and the distinction between full papers and notes**.
* **We allowed authors to write rebuttals before reviews were finalized.** Reviewers and ACs were allowed to modify their reviews and decisions based on rebuttals.
* To assist in assigning papers to ACs and to reviewers, **we made extensive use of bidding**. This means we had to recruit the pool of reviewers before papers were submitted.
```
-The figure above shows scores for each paper submitted. The vertical grey lines reflect the distribution of scores where the minimum and maximum scores for each paper are the ends of the lines. The colored dots show the arithmetic mean for each score (unweighted by reviewer confidence). Colors show whether the papers were accepted, rejected, or presented as a poster. It's important to keep in mind that two papers were *submitted* as posters. Although Associate Chairs made the final decisions on a case-by-case basis, most papers that had an average score of less than 0 (the horizontal orange line) were rejected and most papers with positive average scores were accepted. We ultimately accepted `r num.papers.accepted` papers (`r paste(round(num.papers.accepted / (nrow(submissions) - 2)*100), "%", sep="")`) of those submitted.
+The figure above shows scores for each paper submitted. The vertical grey lines reflect the distribution of scores where the minimum and maximum scores for each paper are the ends of the lines. The colored dots show the arithmetic mean for each score (unweighted by reviewer confidence). Colors show whether the papers were accepted, rejected, or presented as a poster. It's important to keep in mind that two papers were *submitted* as posters. Although Associate Chairs made the final decisions on a case-by-case basis, every paper that had an average score of less than 0 (the horizontal orange line) was rejected and most (but not all) papers with positive average scores were accepted. We ultimately accepted `r num.papers.accepted` papers (`r paste(round(num.papers.accepted / (nrow(submissions) - 2)*100), "%", sep="")`) of those submitted.
# Rebuttals
# This Analysis
-OpenSym used the gratis version of [EasyChair](https://www.easychair.org/) to manage the conference which doesn't allow chairs to export data. As a result, data used in this this postmortem was scraped from EasyChair using two Python scripts. Numbers and graphs were created using a [knitr](https://yihui.name/knitr/) file that combines R visualization and analysis code and markdown. I've made all the code I used to produce this analysis available in [this git repository](FIXME). I hope someone else finds it useful. Because the data contains sensitive information on the review process, I'm not going to publish the data.
+OpenSym used the gratis version of [EasyChair](https://www.easychair.org/) to manage the conference which doesn't allow chairs to export data. As a result, data used in this this postmortem was scraped from EasyChair using two Python scripts. Numbers and graphs were created using a [knitr](https://yihui.name/knitr/) file that combines R visualization and analysis code and markdown. I've made all the code I used to produce this analysis available in [this git repository](https://code.communitydata.cc/opensym2017_postmortem.git). I hope someone else finds it useful. Because the data contains sensitive information on the review process, I'm not going to publish the data.
projects / opensym2017_postmortem.git / blobdiff