MétaCan
Menu
Back to cohort
Record W3147661917 · doi:10.29173/iasl7683

Negotiating the Social Organization of School Library Work

2021· article· en· W3147661917 on OpenAlexvenueno aff
Jennifer Crispin

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationPresentation (obstetrics)InstitutionSociologyWork (physics)Public relationsFrame (networking)Function (biology)EthnographySocial organizationPedagogyPolitical scienceSocial scienceEngineering

Abstract

fetched live from OpenAlex

I investigated how school library work is socially organized and how that social organization affects cooperation with teachers and others in the school. The research uses the institutional ethnography frame of inquiry, providing a way of looking at how the role and function of the school librarian/ school media specialist is socially-organized and institutionally-oriented. The social organization was apparent in the categories of collaboration, technology, and access. A better understanding of how library work is socially organized will help working librarians understand how to negotiate their workplace more effectively. An understanding of how to examine the social organization of an institution can help inform research and teaching in school librarianship as well. This presentation is a follow-up to a presentation at IASL 2008 conference in Berkeley, California.

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0210.028
Scholarly communication0.0170.010
Open science0.0020.015
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.033
GPT teacher head0.286
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueIASL Annual Conference ProceedingsSame topicLibrary Science and AdministrationFrench-language works237,207