CCF Database: A Machine-Learning-Annotated Corpus of 283,964 Canadian Climate Articles (1978–2026) — PostgreSQL edition

The Canadian Climate Framing (CCF) Database: a machine-learning-annotated, sentence-level corpus of 283,964 Canadian climate-change articles from 22 news outlets (1978–2026), processed into 9,908,776 two-sentence analytical units, each carrying 65 hierarchical binary annotations, named-entity extractions, per-article aggregates, per-category reliability tiers, and 10,192,740 BAAI/bge-m3 sentence embeddings.

Release notes (v2.1.0 — the three CCF deposits are aligned on a single version number; the corpus itself is unchanged from v2.0.0): the PostgreSQL edition, the Apache Parquet mirror and the code & documentation deposit had drifted onto different patch numbers while their contents were being corrected. From this release they carry the same version number and are published together. Content changes since v2.0.0 are documentation only: Scripts/Annotation/ holds exactly the seventeen canonical pipeline scripts 01–17 (five superseded copies under an older numbering scheme were removed); the code bundle ships a README.md, a CITATION.cff and a corrected requirements.txt, the first two generated from the manuscript's canonical figures so they cannot drift from the release they document; the archived static training configuration was re-derived from the released training code; and the English base model is correctly identified as bert-base-cased. All row counts, annotations, embeddings and validation metrics are identical to v2.0.0.

The full methodology is described in the accompanying paper (Scientific Data, in revision). Because Canadian newspaper articles are protected by copyright, the deposit does not redistribute full article text; every row is traceable to its source article through complete bibliographic metadata.