MétaCan
Menu
Back to cohort
Record W6947647578 · doi:10.3886/e195005

Data and Code for: Local Productivity Spillovers

2024· dataset· en· W6947647578 on OpenAlexaffabout

Bibliographic record

VenueICPSR Data Holdings · 2024
Typedataset
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsProductivityRevenueSortingQuality (philosophy)SalientProduction (economics)

Abstract

fetched live from OpenAlex

Using Canadian administrative data, this paper presents evidence of revenue and productivity spillovers across firms at fine spatial scales. Accounting for the endogenous sorting of firms across space, we estimate an average elasticity of firm revenue and productivity with respect to the average quality of other firms within 75 meters of 0.024. We find scant evidence that the average firm benefits from being surrounded by a greater amount of economic activity at this spatial scale. Sorting of higher quality firms into more productive locations and higher average and aggregate quality peer groups is salient in the data.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science
Consensus categoriesScholarly communication, Open science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0090.058
Open science0.0310.070
Research integrity0.0000.001
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 head0.208
GPT teacher head0.414
Teacher spread0.206 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueICPSR Data HoldingsSame topicResearch Data Management PracticesFrench-language works237,207