#ICPConcerned: Global Images for Global Crisis
Bibliographic record
Abstract
Publisher's blurb "On March 13, 2020 when the global coronavirus pandemic brought life as we know it to an abrupt halt, the International Center of Photography, just weeks after opening in a brand-new building on Manhattan’s Lower East Side that was buzzing with visitors, was forced to close its doors. Wanting to do more than virtual exhibition tours, ICP announced the #ICPConcerned open call on March 20th, an invitation for people to make, upload, and tag images on Instagram of whatever was going on in their lives wherever they were. What resulted was more than sixty thousand submissions from countries as far flung as France, Singapore, Argentina, Nigeria, Canada, and Iran. \n\nNow, the book #ICPConcerned: Global Images for Global Crisis (October 19, 2021) chronicles the museum’s innovative #ICPConcerned exhibition about which David Campany says,\n\n“This is the story and a celebration of a wild idea, dreamed up in deep uncertainty, at the onset of what turned out to be a tumultuous year.” \n\nFrom the halls of medical facilities to eerily empty streets and domestic settings converted into home offices and classrooms, the more than 800 photographs collected here are organized chronologically and accompanied by headlines gathered from various global news entities. Taken together, these words and pictures represent the pain, heartbreak, hope, and occasional humor we’ve all experienced this past year against the backdrop of COVID-19, unrelenting racial injustice, and a divisive political climate. \n\nMade from hundreds upon hundreds of visions and voices, selected by a team from thousands upon thousands, #ICPConcerned is not only extraordinary images; it is the story of a project which started with a hashtag, became an epic exhibition staged in the middle of a pandemic, and culminated in a book that will forever capture all that we did--and all that we endured--in 2020."\n\nEdited and with and essay by David Campany
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
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 teacher head, 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".