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
Column Editor's Note:The 'like button' is a ubiquitous and infamous feature of social media platforms.'Likes' ostensibly allow users to interact and engage with one another, but platform developers hope that data generated by users' likes allows them to model, predict and even manipulate both individual and collective affective states.This Mining the Past column by communication scholar Carina Albrecht explores the history of the like button from "Little Annie," developed at CBS in the mid-twentieth century, to the Cambridge Analytica scandal.Throughout this history, researchers and tech developers hoped to make 'subjectivities 'emotions, preferences, personalities, political orientations-into 'objectivites'; they sought to turn inner worlds into profitable data.Albrecht's history reveals that the like button is best understood not as a passive recorder of preexisting affect and sentiment, but rather as a data technology that generated the emotive effects the button claimed to measure.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.014 |
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