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Record W4382363284 · doi:10.1117/12.2666795

Students’ reflections on the impact of paid summer photonics research internships

2023· article· en· W4382363284 on OpenAlexafffund
Rhys Adams, Lawrence R. Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicInnovations in Educational Methods
Canadian institutionsMcGill UniversityVanier College
FundersFonds de recherche du Québec – Nature et technologies
KeywordsInternshipPhotonicsComputer scienceEngineering physicsMathematics educationEngineeringMedical educationOptoelectronicsPsychologyMaterials scienceMedicine

Abstract

fetched live from OpenAlex

Getting young and talented minds to pursue photonics as a career is a major goal for the optics and photonics community. We have previously reported on a college-university collaboration allowing pre-university science students to engage in university photonics research through paid summer internships. From the university’s perspective, this collaboration allows for photonics outreach to students before they choose university programs. From the student’s perspective, they are immersed in a scientific research experience for the first time, and they then present their experience in class to the following cohort of college students – this is outreach too. We have surveyed all students who have participated in these paid summer research internships during the first ten years of this collaboration. We report on 1) the survey results to questions pertaining to their learning experience, the training and learning environment, and aspirational elements, and 2) their reflections on the strengths and weaknesses of these internships, such that we can improve the “student experience” for future internships.

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)0.011
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.714
GPT teacher head0.704
Teacher spread0.010 · 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.

Study designTheoretical or conceptual
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
Published2023
Admission routes2
Has abstractyes

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