On the Space/Time of Information Literacy, Higher Education, and the Global Knowledge Economy
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
Local sites and practices of information work become embroiled in the larger imperatives and logics of the global knowledge economy through social, technological, and spatial networks. Drawing on human geography’s central claim that space and time are dialectically produced through social practices, in this essay I use human/critical geography as a framework to situate the processes and practices—the space and time—of information literacy within the broader social, political, and economic environments of the global knowledge economy. As skills training for the knowledge economy, information literacy lies at the intersection of the spatial and temporal spheres of higher education as the locus of human capital production. Information literacy emerges as a priority for academic librarians in the 1980s in the context of neoliberal reforms to higher education: a necessary skill in the burgeoning “information economy,” it legitimates the role of librarians as teachers. As a strategic priority, information literacy serves to demonstrate the library’s value within the university’s globalizing agenda. While there has been a renewed interest in space/time within the humanities and social sciences since the 1980s, LIS has not taken up this “spatial turn” with the same enthusiasm—or the same degree of criticality—as other social science disciplines. This article attempts to address that gap and offers new insights into the ways that the spatial and temporal registers of the global knowledge economy and the neoliberal university produce and regulate the practice of information literacy in the academic library. Pre-print first published online 12/09/2018
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.029 |
| Open science | 0.000 | 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