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Record W2547601501 · doi:10.5539/hes.v6n4p70

Factors Influencing Teachers in Engaging with University Outreach: Is it Just Cost?

2016· article· en· W2547601501 on OpenAlexvenueno aff
Sarah R. Glover, Tim Harrison, Dudley E. Shallcross

Bibliographic record

VenueHigher Education Studies · 2016
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachEvent (particle physics)Value (mathematics)Quality (philosophy)Subject (documents)PsychologyMedical educationMathematics educationPedagogyPublic relationsMedicinePolitical scienceLibrary sciencePhysicsComputer science

Abstract

fetched live from OpenAlex

A chemistry outreach day event was offered, free-of-charge, to schools in the south west of England who do not normally engage with Bristol ChemLabS outreach events delivered at the University of Bristol. The participating teachers were interviewed to find out their expectations of the day in terms of helping their students or in helping the teachers, whether the “free” aspect, or not, triggered the application to the event and whether finance or other barriers normally prevented engagement in such events. The value versus cost of such outreach an event is discussed. While finance was the biggest issue for the majority of the interviewed teachers they recognised the value of the inspiration rather than subject knowledge acquisition for their students. The advantages for the teachers were seen as better motivated students and the likelihood of more students taking their subject at higher levels. Having attended such an event and observing the quality and impact on their students, teachers were more inclined to engage in the future whether there was a financial charge or not.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.168
GPT teacher head0.375
Teacher spread0.207 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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