Bibliographic record
Abstract
Purpose This paper aims to discuss traditional conceptions of information literacy as created within an academic context to address information needs within this context. It seeks to present alternative realities of information use outside the academic sector, and to suggest that information literacy instruction within academia does not go far enough in preparing students for the information society beyond university. The aim is then to follow this by discussion of appropriate information literacy models to prepare young people for information use in a variety of workplace environments. Design/methodology/approach As an example of the application of appropriate information literacy models for successful workplace information use, the Edmonton Social Planning Council youth internship program is examined through a case study of two successful internship projects. Findings This youth internship program provides young people with skills that are highly relevant to their information environment outside the academic sector. It provides them with a framework for interacting with information that can be applied in any academic or non‐academic setting in which they find themselves. Practical implications The program described could serve as inspiration for other public, private or nonprofit organizations to collaborate on similar initiatives. It also serves to remind academic librarians of core information best practices that must be conveyed through library instruction if students are to become good information citizens. Originality/value While information literacy instruction receives much attention in the academic sphere, it is necessary to take a broader view of information use throughout the lifetime of information users and the instruction required to prepare students adequately. The paper focuses on these issues.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".