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Record W3140736179 · doi:10.29173/iasl7738

The Information Search Process (the ISP) and the research essay

2021· article· en· W3140736179 on OpenAlexvenueno aff
Helen Reynolds

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Assessment and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsInformation literacySet (abstract data type)Process (computing)PedagogySociologyLibrary scienceMathematics educationEngineering ethicsPsychologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Queensland Academy for Health Sciences (QAHS) is a senior secondary high school offering the International Baccalaureate (IB) Diploma Programme (DP). As part of the Diploma, students are required to complete a referenced research essay of four thousand words. For most, this will be their first experience of such a challenging undertaking. Problematic are the varying levels of student information literacy expertise, especially in the area of research. The challenge is to provide students with the tools to enable them to complete the essay within the guidelines set down by the IB Organisation. Kuhlthau’s ISP (Kuhlthau 2009) has been adapted to provide students with a research structure.

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)0.033
metaresearch head score (Gemma)0.143
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.143
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0040.004
Scholarly communication0.0110.014
Open science0.0020.008
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0360.020

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 head0.095
GPT teacher head0.448
Teacher spread0.353 · 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.

Study designNot applicable
DomainMethods
GenreMethods

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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Citations0
Published2021
Admission routes1
Has abstractyes

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