Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Does teaching experience increase teacher effectiveness? A review of US research
2019139 citationsAnne Podolsky, Tara Kini et al.Journal of Professional Capital and Communityprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Anne Podolsky's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Anne Podolsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anne Podolsky more than expected).
This network shows the impact of papers produced by Anne Podolsky. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Anne Podolsky. The network helps show where Anne Podolsky may publish in the future.
Co-authorship network of co-authors of Anne Podolsky
This figure shows the co-authorship network connecting the top 25 collaborators of Anne Podolsky.
A scholar is included among the top collaborators of Anne Podolsky based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Anne Podolsky. Anne Podolsky is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Podolsky, Anne, Linda Darling‐Hammond, Christopher Doss, & Sean F. Reardon. (2019). California’s Positive Outliers: Districts Beating the Odds.8 indexed citations
3.
Podolsky, Anne, Linda Darling‐Hammond, Christopher Doss, & Sean F. Reardon. (2019). California's Positive Outliers: Districts Beating the Odds. Positive Outliers Series..1 indexed citations
Darling‐Hammond, Linda, Jeannie Oakes, Maria E. Hyler, et al.. (2019). Preparing Teachers for Deeper Learning (research brief)..5 indexed citations
8.
Podolsky, Anne, Tara Kini, & Linda Darling‐Hammond. (2019). Does teaching experience increase teacher effectiveness? A review of US research. Journal of Professional Capital and Community. 4(4). 286–308.139 indexed citations breakdown →
9.
Reardon, Sean F., et al.. (2018). Gender Achievement Gaps in U.S. School Districts. CEPA Working Paper No. 18-13..3 indexed citations
Podolsky, Anne & Tara Kini. (2016). How Effective Are Loan Forgiveness and Service Scholarships for Recruiting Teachers? Policy Brief..8 indexed citations
14.
Kini, Tara & Anne Podolsky. (2016). Does Teaching Experience Increase Teacher Effectiveness? A Review of the Research. Research Brief..2 indexed citations
15.
Reardon, Sean F., et al.. (2016). Geographic Variation of District-Level Gender Achievement Gaps within the United States.. Society for Research on Educational Effectiveness.2 indexed citations
16.
Podolsky, Anne & Leib Sutcher. (2016). California Teacher Shortages: A Persistent Problem..11 indexed citations
17.
Reardon, Sean F., et al.. (2016). Test Format and the Variation of Gender Achievement Gaps within the United States.. Society for Research on Educational Effectiveness.1 indexed citations
18.
Podolsky, Anne, et al.. (2016). Evidence-Based Interventions: A Guide for States.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.