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Record W6990191747

DC best place for grads to start a career

2015· other· en· W6990191747 on OpenAlexaboutno aff

Bibliographic record

VenueInternet Archive (Internet Archive) · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNightlifeUnemploymentFace (sociological concept)EntertainmentWork (physics)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

College grads might want to head to Washington DC. Forbes has ranked the nation's capitol as the top city for 20 something's to launch their careers. Minneapolis is #2 followed by Denver and San Francisco. Forbes looked at the number of jobs in the cities, the unemployment rate and the average cost of living. In other studies, Rent.Com looked at US cities with populations of more than 100,000 and found DC the easiest for people age 20-34 to afford. They also factored in the availability of restaurants, bars, nightlife and entertainment opportunities. The top three most-populous cities, New York, Los Angeles and Chicago, didn’t make the cut. And CareerBliss.com looked at the 10 happiest cities for job seeking college grads when it comes to cost of living and entertainment. St Louis was #1. Salt Lake City and Jacksonville, Florida were #2 and 3. Other places most likely to keep a smile on a young person's face were Memphis, Indianapolis, Orlando, Houston, San Antonio, Oklahoma City, and Birmingham, Alabama.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.210
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0040.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.069

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 head0.035
GPT teacher head0.278
Teacher spread0.243 · 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
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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