Data cultures: Contested meanings in a public cultural institution
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
This paper maps the configurations of meanings surrounding data culture and examines its ongoing transformation. Using the National Library and Archives of Quebec (BAnQ) as a case study, it explores the interplay between practices and interpretations of what constitutes data culture within this public cultural institution. Rather than approaching data culture as an entirely new set of dispositions that organizations need to develop, I propose understanding it as a contested field of meanings. This field brings together heterogeneous elements—some grounded in long-established professional practices, others emerging in response to new digital demands—where divergent logics of action and values collide. Rooted in critical data studies, this paper offers empirical insights into the power dynamics within data cultures, conceptualized as complex arrangements of meanings, material apparatuses, and social practices. It identifies key factors that shape data culture at the BAnQ: organizational structures, professional values, institutional goals (such as artifact documentation, public accessibility, and performance optimization), governmental requirements, and data tools and ideologies. The formation and transformation of data culture at the BAnQ appear to be a dynamic process that requires aligning new practices with existing frameworks of meaning, while also exposing tensions and resistance among differing interpretations. From this perspective, data culture emerges as an arena of debate, leading to genuine disagreements over the data practices required to fulfill the BAnQ's broader mission. As the institution navigates the challenges of datafication, its approach to data governance becomes pivotal in balancing public service goals with the imperatives of data innovation.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.005 | 0.005 |
| 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