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Record W2384604672

On Carrying out Scientific Research of Vocational College and Methods

2014· article· en· W2384604672 on OpenAlexaff
Xiangyang Li

Bibliographic record

VenueThe Guide of Science & Education · 2014
Typearticle
Languageen
FieldComputer Science
TopicHigher Education and Teaching Methods
Canadian institutionsLa Cité Collégiale
Fundersnot available
KeywordsVocational educationQuality (philosophy)Mathematics educationSubject (documents)Process (computing)Vocational schoolEngineering ethicsEngineeringPsychologyPedagogyComputer scienceLibrary science
DOInot available

Abstract

fetched live from OpenAlex

Higher vocational school teachers both teaching and research is increasingly significant, scientific research has not only become an important part of vocational teachers' job classification, is also an important indicator of Vocational School assessment level of scientific research. Here, first pointed out the construction and upgrading of teachers are science and engineering research and improving vocational colleges to carry out an important prerequisite for scientific research, and can be used within the outer lead training approach to improve the quality of teachers. Then, for the science and engineering of particularity, proposed the establishment of a team on the existing basis, choose the subject, to carry out specific research topics and methods, and to propose methods for science and engineering research vocational assessment, namely the process, heavy achievements, light practice assessment methods, in order to lead the polytechnic vocational school teachers, and even other professional vocational school teacher, to answer fundamental problems of carrying out vocational school research.

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)0.038
metaresearch head score (Gemma)0.033
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: Methods · Consensus signal: Methods
Teacher disagreement score0.038
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.004
Science and technology studies0.0040.004
Scholarly communication0.0070.004
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.006

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 head0.120
GPT teacher head0.511
Teacher spread0.391 · 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
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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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