Bibliographic record
Abstract
In this paper, I introduce a new term, adoptism, to characterize the unique form(s) of marginalization to which adopted persons are subjected. Adoptism shows up primarily as enforced gratitude, and this injunction to be grateful carries with it epistemic harms that have heretofore been overlooked because the dominant social narrative surrounding adoption is that it is an overwhelmingly positive practice. This dominant view stems largely from adoptive parents and the adoption industry, which is an institution, I argue, that is far from child-centered and beneficent. Because those most impacted by being adopted, adopted persons, are conspicuously absent in discussions of adoption, there is a great potential for epistemic injustice. These injustices are magnified when adoptees attempt to provide testimony that challenges the prevailing social script surrounding adoption. Using my lived experience as a domestic adoptee, as well as the testimony of many other adopted persons, I uncover and examine the ways adoptees are harmed in our capacities as knowers. Finally, after dispelling the myths that adoptist ideology upholds, I suggest ways to redress the otherwise hidden injustices of adoption.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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; both teacher heads agree on what is shown here.
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".