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Record W3215469055 · doi:10.23977/aetp.2021.59008

The Status Quo and Strategies of Public-funded Normal Students' Identity of Rural Teachers' Profession

2021· article· en· W3215469055 on OpenAlexvenueno aff
Na Wei

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Status quoCornerstonePsychologyPedagogyProfessional developmentIdentification (biology)Medical educationPolitical scienceMedicineLaw

Abstract

fetched live from OpenAlex

Teachers' professional cognition is the spiritual cornerstone of students as an excellent teacher. It is the source of the basic strength of the teacher’s career and the most basic psychological preparation for the teacher's career. If we want to cultivate good teachers and normal students, we must first make students appreciate and accept the profession of teachers. Only in this way, students can devote themselves to the position of teacher with a more active and pleasant attitude, relieve all kinds of pressures and problems, strengthen students' identification with the teacher profession, and help students fall in love with this profession. This article researches the status and strategy of the professional identity of rural teachers of publicly funded normal students. After understanding the relevant theories about the professional identity of rural teachers of publicly funded normal students on the basis of literature data, it investigates the current situation of the professional identity of rural teachers of publicly funded normal students. According to the survey results, the professional identity of public-funded normal students at this stage is low, and the basic dimensions of professional identity are all lower than the theoretical median. Among the suggestions for improving professional identity, relevant policies have been introduced to improve the relevant treatment of teachers accounted for 45 %about.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.381
Teacher spread0.355 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2021
Admission routes1
Has abstractyes

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