Handshake, No. 16 (June 2015) : A Public-Private Partnerships Journal
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The latest issue of Handshake, focused \n on public-private partnerships in the Innovation. “An age of \n constant invention naturally begets one of constant \n failure,”the New York Times Magazine declared in a recent \n story called “Welcometo the Failure Age.” Its core \n premise—that innovation is inextricably linked with \n failure—may be a fresh insight for the high-tech era, but \n has long been understood by those who work in \n infrastructure. To state the obvious:for those of us in \n infrastructure PPPs, failure is not a novel \n concept.Innovation is. The interplay between the two, with \n attention to the iterativelearning that is necessary to \n morph missteps into course corrections. Once the seeds of \n those ideas are planted, innovation has already begun to \n germinate. This issue includes the following headings: \n inside Korea’s PPP unit reinvigorating the regional economy; \n innovating at scale less early adoption,more global \n adaptation; The politics of PPP barcelona partnership \n energizes urban center; redefining failure and success why \n the “Brilliant Mistake” matters; course corrections small \n changes that create better outcomes; reviving the reliance \n rail PPP turning around a difficult project; protecting your \n PPP stabilizing partnerships in uncertain times; PPP insider \n Korea’s PPP unit creates institutional memory; from lessons \n to principles The public governance of PPPs; money talks \n debunking the myth of the “quick and easy” PPP; inside \n infrastructure powering rural Africa; One question eight \n experts discuss how PPPscan absorb common mistakes; master \n class preventing renegotiation, fostering efficiency; What \n the rest of the world is saying about PPPs.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.110 | 0.150 |
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 it