Through a glass darkly: Researching workplace discrimination using an identity meta-perception (IMP) lens
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
This paper presents findings based on a novel approach to researching identity and inequality in the workplace. Our research results from a large survey of camera department employees in the Australian screen industry. Workers were invited to self-nominate various personal identifications, but also to tell us how they thought they were perceived by others. With this information we analysed workplace discrimination in terms of the various possible interconnections between identity self-perception and meta-perception (what people believe other people think about them). We found a clear link between specific forms of discrimination in camera departments and discordant experiences of identity in which workers did not feel there was an alignment between the way they self-identify and the meta-perception of these identities by colleagues. This link was particularly pronounced for people experiencing homophobia and/or ableism. We also found that ignorance of workplace discrimination was highest among cohorts with highly aligned self- and identity meta-perceptions.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it