Editor’s Introduction
Bibliographic record
Abstract
The image that undoubtedly captures the embodied reality of living in the ‘post-pandemic’ world as a Black grad student is the viral blurry Mr. Krabs meme surrounded by an angry mob[i]—yeah, that one! I have no idea what’s going on academically—I haven’t fully recovered from the plague of Black death that has become ‘the newly designated disposable bodies of the pandemic’ –my world has shaken. This meme encapsulates the disorientated state I currently occupy. The once urgent and ignited public discourse regarding systemic police reforms are now stagnant, thwarted by state and public debates of the vaccinated vs. unvaccinated that places responsibility on BIPOC to stop the spread of COVID-19. In the ‘post-pandemic world’, death and freedom are immutably interwoven; the freedom to die is set above the unfreedom of containment and ‘forced’ vaccinations—and the freedom to live longer; relatively free, is through the unfreedom of mobility. So, what does life feel like as a Black grad student navigating social media/public feeds that choose to strip colonial, racist, and imperialist histories from strict biopolitical regimes of COVID-19 containment in Canada and at York University? It feels suffocating—it is violent. - Beatrice Anane-Bediakoh, Chief-Deputy-Editor These days, COVID-19 is consistent background noise, while the movements for racial justice are distant memories. We’re so distracted by technology; we don't hear the stories of tragedy or hear the politicians lie casually when they promise change passionately – do those ideas ever really come to life? Time passes and the masses’ attention turns to the next day, but the next day brings Black, Indigenous and People of Colour dying in daylight. So much pain, too many emotions, and just to listen, is a fight. Time is life and these days that’s a luxury. So today, I sit here daydreaming and realize that tomorrow brings the best yet to come. So tonight, I lay here dreaming of an otherwise that fights the tragedy of reality. All while thinking of my son, holding him close, so I don’t let him drown, so I don’t let him down. - Giovanni Carranza- Hernandez, Chief-Deputy-Editor I don’t know what time is. I have long joked that “time is a construct.” It’s an occupational hazard to make such philosophical declarations. But now, I feel the words in my marrow. Was it not a minute ago, that everyone cared about the state sanction killing of Black and Indigenous folx and PoC? Was 2019 not last week, a few sleepless nights away? When was it, that my home went from a mundane reality to an uncanny fact of life? When did today stop being tomorrow? Being Brown, a grad student, queer, enby, femme, it’s always timeless, but now, time is the chokehold of staying still and propelling simultaneously. I am me tomorrow, yesterday, today. I am the construction to which I used to attribute time. - Jade Crimson Rose Da Costa, Founder/Editor-in-Chief
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 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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.465 | 0.289 |
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".