Equality of Retrieval: Leveling the Metadata Playing Field in Big Indexes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The University of Calgary's Libraries and Cultural Resources became a beta partner with Serials Solutions’ unified discovery service, Summon, in the spring of 2009. Since then it has worked to include metadata from numerous disparate systems in a single index to drive discovery in a Google-like environment. The University has examined how MARC and other metadata schemas are mapped into Summon with an eye to ensuring the maximum possible population of index fields representing facets in addition to adhering to the established standards for cross mapping metadata schemas and indexing. It has investigated existing standards and worked closely with the Summon team to create mappings that reflect how MARC and other metadata can ultimately be used in big indexes. Combined with the normalization or collapsing of metadata records representing the same resource into a single metadata-rich record, fully leveraging MARC and other metadata in big indexes should not only level the metadata playing field but make competition between records a non-issue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it