Social discovery tools: extending the principle of user convenience
Bibliographic record
Abstract
Purpose New social discovery systems have social‐type Web 2.0 features that allow users to enhance the content of bibliographic records by adding their own tags, ratings, and reviews. One of the primary underlying principles of cataloguing is that catalogue records be designed with the user in mind, i.e. user convenience. The purpose of this paper is to explore the relationship between the principle of user convenience and social discovery systems. Design/methodology/approach A review of the literature and codes of ethics of associations of information professions was undertaken to examine: the ethical dimensions of creating catalogue records to reflect user convenience, the relationship between culture and user convenience, and how social discovery tools can facilitate the creation of interactive and flexible catalogue records that reflect the culture(s) and needs of the library communities in which they exist. Findings Social discovery systems can address the primary barriers to creating catalogue records that meet user convenience: determining and reflecting the needs and cultural warrant of the users, and maintaining the quality and integrity of the catalogue records. Practical implications Social discovery systems can serve as a bridge between cataloguers' desire to create accurate catalogue records that conform to accepted cataloguing standards, and their ethical imperative to ensure that these records meet the needs of the clients. Originality/value The findings of this study pave the way for further research into how user‐contributed metadata allow clients to express their needs and cultural warrant and to interact with one another and library staff.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.059 | 0.122 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.008 | 0.032 |
| Scholarly communication | 0.023 | 0.036 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".