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Record W4398504684 · doi:10.7910/dvn/kldwd8

Back-to-School Data

2022· dataset· en· W4398504684 on OpenAlexaff
Blake Lee‐Whiting, Thomas Bergeron

Bibliographic record

VenueHarvard Dataverse · 2022
Typedataset
Languageen
FieldDecision Sciences
TopicEducational Assessment and Improvement
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

To better understand the preferences of post-secondary students, we surveyed 4,812 students in 78 countries who attend over 1,000 unique post-secondary institutions between July 28 and August 27, 2021. We fielded this survey on the Qualtrics survey platform using targeted social media advertising to acquire a convenience sample. We administered the survey in English, French, Spanish, Korean, and Portuguese, and oriented the sampling towards countries where at least one of these languages is dominant. The survey sample has not been weighted. We acknowledge that a survey of this breadth may not accurately indicate country or region-level with great accuracy.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.227
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0110.011
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.9720.745

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 head0.149
GPT teacher head0.408
Teacher spread0.259 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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