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Record W2980291088 · doi:10.29173/iasl7428

I may not be a librarian, but I’m running the school library

2019· article· en· W2980291088 on OpenAlexaffvenueabout
Norene Erickson

Bibliographic record

VenueIASL Annual Conference Proceedings · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsMacEwan University
Fundersnot available
KeywordsFeelingSchool libraryConstruct (python library)Work (physics)Identity (music)Value (mathematics)PsychologySociologyPedagogyLibrary scienceSocial psychologyEngineeringComputer scienceArt

Abstract

fetched live from OpenAlex

Work identity is defined as ones’ sense of purpose, value and belonging in the workplace (Saayman & Crafford, 2011). It is a useful construct in which to investigate how identities are influenced and developed through personal characteristics, relationships, and work activities. This study sought to understand the ways in which school library paraprofessionals’ work identities are formed. Seven library paraprofessionals in Alberta, Canada were interviewed as to their experiences working in a school library. It was discovered that, despite experiencing some misconceptions about their ability, sometimes feeling disconnected with others in the school and lacking a voice to direct their own work, these paraprofessionals experienced a sense of purpose, value and belonging at work. This study demonstrates that even if library paraprofessionals are not qualified Teacher-Librarians, they still are deeply committed to making a difference in the lives of young students.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.006
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0210.007

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 head0.030
GPT teacher head0.291
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations1
Published2019
Admission routes3
Has abstractyes

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