{"doi":"10.1146/annurev-statistics-031219-041104","title":"Calibrating the Scientific Ecosystem Through Meta-Research","abstract":"<jats:p>While some scientists study insects, molecules, brains, or clouds, other scientists study science itself. Meta-research, or research-on-research, is a burgeoning discipline that investigates efficiency, quality, and bias in the scientific ecosystem, topics that have become especially relevant amid widespread concerns about the credibility of the scientific literature. Meta-research may help calibrate the scientific ecosystem toward higher standards by providing empirical evidence that informs the iterative generation and refinement of reform initiatives. We introduce a translational framework that involves ( a) identifying problems, ( b) investigating problems, ( c) developing solutions, and ( d) evaluating solutions. In each of these areas, we review key meta-research endeavors and discuss several examples of prior and ongoing work. The scientific ecosystem is perpetually evolving; the discipline of meta-research presents an opportunity to use empirical evidence to guide its development and maximize its potential.</jats:p>","journal":"Annual Review of Statistics and Its Application","year":2020,"id":12321,"datarank":2.4161946482154235,"base_score":4.59511985013459,"endowment":4.59511985013459,"self_citation_contribution":0.6892679775201885,"citation_network_contribution":1.7269266706952349,"self_endowment_contribution":0.6892679775201885,"citer_contribution":1.7269266706952349,"corpus_percentile":null,"corpus_rank":null,"citation_count":98,"citer_count":77,"citers_with_citation_signal":60,"citers_with_endowment":60,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0479,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-03-09","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1621,"name":"Stylianos Serghiou","orcid":"0000-0002-2477-6060","position":1,"is_corresponding":false},{"id":3831,"name":"Perrine Janiaud","orcid":"0000-0001-7684-8014","position":2,"is_corresponding":false},{"id":20384,"name":"Valentin Danchev","orcid":"0000-0002-7563-0168","position":3,"is_corresponding":false},{"id":11433,"name":"Sophia Crüwell","orcid":"0000-0003-4178-5820","position":4,"is_corresponding":false},{"id":3919,"name":"Steven N. Goodman","orcid":"0000-0002-3872-5723","position":5,"is_corresponding":false},{"id":148,"name":"John P. A. Ioannidis","orcid":"0000-0003-3118-6859","position":7,"is_corresponding":false},{"id":875,"name":"Tom Elis Hardwicke","orcid":"0000-0001-9485-4952","position":0,"is_corresponding":true}],"reference_count":200,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}