Reaching Out, Reaching In: A Preliminary Investigation into Archives’ Use of Social Media in Canada
Bibliographic record
Abstract
This paper reports on two preliminary studies that investigated aspects of archives’ use of social media: an environmental scan of Canadian archives and a focus group study of archival users. The environmental scan examined the use of social media by 648 archives and noted the degree of user engagement with a selection of social media services. The data were collected over a two-month period, from 11 November 2011 to 10 January 2012. The focus group study consisted of five sessions, each with four to seven participants, for a total of twenty-eight participants. The studies found that, with a few exceptions, archives were making minimal use of social media to attract users, user engagement was still relatively low, and the participants in the study had a number of concerns about contributing to social media. However, the participants in the focus groups also saw the potential for social media to democratize the archives, contribute to the public good, allow for a richer historical record showing different points of view, and, ultimately, increase their engagement with archives. RÉSUMÉ Ce texte rend compte de deux enquêtes préliminaires qui ont examiné des aspects de l’utilisation que font les archives des médias sociaux : un bilan de l’environnement des archives canadiennes et une étude d’un panel d’utilisateurs des archives. Le bilan s’est penché sur l’utilisation des médias sociaux par 648 centres d’archives et a noté le degré d’engagement des utilisateurs avec une sélection de services des médias sociaux. Les données ont été recueillies sur une période de deux mois, du 11 novembre 2011 au 10 janvier 2012. Le panel d’utilisateurs des archives comprenait cinq sessions, chacune avec quatre à sept participants, pour un total de vingt-huit participants. Les enquêtes ont révélé qu’à quelques exceptions près les centres d’archives font une utilisation minime des médias sociaux pour attirer des utilisateurs des archives, l’engagement des utilisateurs demeure toujours relativement bas et des participants à cette étude ont un certain nombre de préoccupations par rapport à leur contribution aux médias sociaux. Cependant, les participants du panel voient aussi le potentiel des médias sociaux pour démocratiser les archives, pour contribuer au bien public, pour donner aux documents d’archives une plus grande richesse en permettant différents points de vue et ultimement, pour augmenter leur engagement avec les archives.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".