School Library Media Specialists' Use of Time: A Review of the Research
Bibliographic record
Abstract
Various research studies have attempted to categorize the tasks performed by school library media specialists and the time devoted to them. Since 1969, approximately a dozen studies have been conducted in the United States and one in the United Kingdom. The number of participants in these studies ranged from fewer than 10 per study to several hundred. Diverse methodologies have been employed to collect the data, including diaries, surveys, logs, work sampling, estimating, and observation. In some cases, researchers wanted to ascertain simple distributions of how school library media specialists spent their time, but others have focused on how outside influences such as automation, scheduling, and support staff affect time use.
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How this classification was reachedexpand
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.029 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.050 | 0.002 |
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; both teacher heads agree on what is shown here.
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".