Overall, the paper is progressing well and offers a well-structured analysis of an important issue!
Strong Positive Points
• The abstract is well-written, clearly laying out what was done (analyzing shelter resident deaths), what was found (increasing deaths, particularly in winter months), and why this matters (to support targeted interventions for vulnerable populations). The abstract is concise and covers the necessary points.
• The data section is robust and transparent, providing a good understanding of the dataset, how it was cleaned, and the statistical measures used to interpret it. The description of the seasonal and annual trends is well-supported by the data and graphs.
• The results and discussion sections offer a clear narrative on trends, emphasizing both the seasonal and long-term aspects of shelter deaths.
Critical Improvements Needed
README.md and LLM Usage:
o Ensure that the README.md file is updated to reflect the goals of the paper. Include a note about whether AI or LLM tools were used during the writing or coding process to ensure transparency.
Data Assumptions:
o In the "Data Measurement" section, add more context on how shelter resident deaths are reported. For example, a detailed explanation of the methods used by Toronto Public Health or any potential biases in data collection would enhance the reliability of the conclusions drawn.
Clarification on Models Used:
o The linear regression model is mentioned, but the rationale for its use could be elaborated upon. Are there other models that could have been applied, and why was linear regression chosen specifically for this analysis?
Suggestions for Improvement
Graphs and Visuals:
o Ensure consistency in the design of the graphs. Titles, axis labels, and legends should use similar styles for easier reading. Some graphs have different visual themes, and aligning them with a single visual style would enhance the overall presentation.
Expand on Limitations:
o The limitations section can benefit from a deeper discussion of the potential underreporting of deaths, especially in cases where shelter residents may not be easily identifiable.
Abstract Detail:
o While the abstract is strong, consider adding a brief sentence to clarify what is meant by "changing needs." Specify which aspects (healthcare, housing, etc.) are of most concern in addressing the rising shelter resident deaths.
Evaluation:
The paper is well-written and structured, with clear data-backed insights on shelter resident mortality trends. By refining the abstract, addressing transparency on LLM use, and adding further context to the data assumptions, the paper will gain both clarity and depth.
With these improvements, the paper can be elevated further to provide clearer insight into shelter resident deaths and the policy implications that follow. Keep up the great work!
HaoweiFan0912
commented
6 days ago
Overall, the paper is progressing well and offers a well-structured analysis of an important issue!
Strong Positive Points • The abstract is well-written, clearly laying out what was done (analyzing shelter resident deaths), what was found (increasing deaths, particularly in winter months), and why this matters (to support targeted interventions for vulnerable populations). The abstract is concise and covers the necessary points. • The data section is robust and transparent, providing a good understanding of the dataset, how it was cleaned, and the statistical measures used to interpret it. The description of the seasonal and annual trends is well-supported by the data and graphs. • The results and discussion sections offer a clear narrative on trends, emphasizing both the seasonal and long-term aspects of shelter deaths.
Critical Improvements Needed
Suggestions for Improvement
Evaluation: The paper is well-written and structured, with clear data-backed insights on shelter resident mortality trends. By refining the abstract, addressing transparency on LLM use, and adding further context to the data assumptions, the paper will gain both clarity and depth.
Estimated Mark: 58/64
Rubric: • R is appropriately cited: 1 • LLM usage: 1 • Title: 1 • Author, date, repo: 2 • Abstract: 4 • Introduction: 4 • Data: 8 • Measurement: 2.5 • Prose: 4 • Cross-references: 1 • Graphs: 2 • Referencing: 4 • Commits: 2 • Sketches: 2 • Simulation: 4 • Tests: 4 • Reproducibility: 2 • Code Style: 1
With these improvements, the paper can be elevated further to provide clearer insight into shelter resident deaths and the policy implications that follow. Keep up the great work!