‘The Art of Connection’: a report on the ISC/SCI 2024 online conference
Bibliographic record
Abstract
The Indexing Society of Canada/Société canadienne d’indexation (ISC/SCI) held its 2024 virtual annual conference on 30 May and 1 June. The theme was ‘The Art of Connection’ and around 100 people registered in order to connect with colleagues from around the world. The seven main sessions ranged widely, from practical advice on indexing multi-author texts and on useful non-indexing software to accounts of running an indexing business while travelling the world and on becoming a successful indexer almost by chance, from very humble beginnings. In addition to the pre-conference software sessions, there was a report on a survey into why (or why not) indexers were embracing embedded-indexing techniques. Broadening participants’ horizons, the parallels between indexing and qualitative research were examined, and the conference concluded with a guided discussion on how to advocate for indexers and the indexing profession. In between the main sessions there were opportunities for networking and discussion in breakout rooms and during a quiz, and participants were encouraged to look after their health and well-being during two movement sessions.
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.
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 | 0.024 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.024 | 0.005 |
| Scholarly communication | 0.025 | 0.014 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.058 | 0.011 |
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".