Combined School/Public Libraries in Israel at the Elementary School Level: Some Results of an Exploratory Field Study
Bibliographic record
Abstract
The study aimed to empirically investigate the combined school-public libraries existing at the elementary school level in Israel, compared to regular school libraries. The main research took were three different written closed questionnaires sent to the school librarian, school principal and one of the school teachers. In 1996 questionnaires were mailed to all 130 elementary schools which, according to official government records, had some type of combination libraries. Questionnaires were also mailed to 33 randomly-chosen schools, having a 'regular' (i.e. not combined) library, to serve as a control group. Response rate was about 55% and the final sample included 86 libraries. Main findings: The number of combined libraries has risen constantly over the decades, an interesting trend, especially in view of the recent decline reported in the US and Canada. However, it is likely that the trend has already peaked and the accelerated growth of the 1980's will not recur. Regarding space, seats and collection size, the situation in the main regional combined libraries (typical to rural areas), excluding branches, was much better than in the urban ones, whether combined or not. It is uncertain, however, whether the full potential of these larger dimensions was actually utilized and to what extent elementary school students truly benefited from them. The advantage of the combined libraries is manifested also in the professional searching tools offered to users, but the mean number of users of the reading-room was about the same in most types of libraries for the morning period, but differed considerably in the afternoons. Regarding an overall evaluation: more than half the librarians of the combined libraries rated them as 'very sucessful' and recommended the model to other schools, while the rest (47%) rated it as only 'partially successful' or expressed dissatisfaction due to serious problems, and would recommend it 'with reservation' (36%) or not at all (11%). Findings indicated that the combined model is more likely to succeed in a regional library than in an urban one, and that in most indicators it rates high above the regular libraries included in the control group. However, the relatively high proportion of librarians and principals who avoided rating their combined model as 'vey successful' calls for further and more detailed investigation of the reasons to this finding.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".