The Civil Works Administration :
Bibliographic record
Abstract
A d m in istra tio n , Tennessee V alley A u th o rity , C iv ilia n Con se r v a tio n Corps, and A g ricu ltu r a l Adjustment A d m inistration are on ly a few of the many New Deal a g en cies that are w e ll knovm to stu d en ts of recent American h is t o r y .Much has been said and w r itte n about them, both in p r a ise and condemnation.Each has i t s in te r e s t in g h is t o r y , r e v e a lin g variou s a sp e c ts o f the R oosevelt era .The C iv il Works A d m in istration , com monly knovm as the CWA, has been, however, la r g e ly overlooked by many vnriters on the Great D epression.N eglect of t h is e a r ly New Deal e n te r p r ise is u nd erstandable, fo r i t e x is t e d on ly four and a h a lf months, and, although n early a b i l l i o n d o lla r s were spent in i t s short o p e r a tio n a l p eriod , i t was soon dwarfed by the expenses and achievem ents of ensuing New Deal m easures.N ev erth eless the CW A m erits a c lo s e r a n a ly s is than i s u s u a lly g iven to i t .A bold experim ent, i t was the f i r s t attem pt by the fe d e r a l government to g iv e work to the unemployed in stea d of aid in g the s t a t e s in the problem of r e l i e f .It served as a precedent fo r la t e r and la r g e r fe d e r a l l y sponsored work programs.A c lo s e r study of i t s o b je c t i v e s , as w e ll as i t s shortcom ings and s u c c e s s e s , is i i i w orthw hile fo r th e in s ig h t afford ed in to many a sp e c ts of the dom estic p o l i c i e s of F ranklin R o o sev elt.The w r ite r w ishes to thank h is su p er v iso r, Dr. G ilb ert C. F i t e , fo r h is constant encouragement and su gges t io n s .Thanks are a ls o expressed to th e members of h is committee who read the d is s e r t a t io n and made su g g e stio n s fo r i t s improvement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.119 | 0.025 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".