By Clement C. Camposano, PhD

[Plenary presentation delivered at the 2026 Visayas Regional Scientific Meeting of the National Academy of Science and Technology, with the theme: UN SDGs: Science, Technology, and Innovation for Sustainable Development; June 3, 2026, Summit Hotel, Tacloban City, Leyte]

This paper locates the problem of participation in science within the broader processes of exclusion in education. Exclusion in science is part of the mechanism that reproduces the system of inequality in the country, a system that is very much in place despite a law that provides universal access to tertiary education. When free college education began in 2017, SUC enrollment already favored middle-class students because academic filters convert class advantage into access, including access to science, with PIDS modeling showing that subsidies would flow disproportionately to the richest 40% rather than the poorest 40% (Reyes et al., 2017, para. 6). CHED’s 2018 prioritization policy confirmed this link by reserving slots for 4Ps (conditional cash transfer) beneficiaries and those in the goverent database of poor households. Free tuition, without prioritization, will have the effect of reproducing the same differential access that work to restrict who may participate in both higher education and in science, in favor of those with middle class backgrounds.

Introduction

This presentation is a deliberate mental provocation. Indeed, my intention is to unsettle the way many of us think about science and education, using a critical sociological – and to a more modest extent, anthropological – lens. I shall proceed by locating science within the context of Philippine education, and in the process interrogate the oft-repeated claim that education is the great equalizer. I shall argue that education, and surely science too, function to reproduce the prevailing system of inequality in the country. Allow me to preview the argument: science is elitist because education is. Participation in science is a function of academic success, and there is good evidence to show that the strongest factor behind academic success is, in fact, socioeconomic status (SES).

Exploring the evidence

In the Philippines, the link between SES and academic performance is sharper than in most OECD countries. PISA 2018 showed that SES explained 18% of variance in reading performance in the Philippines versus 12% across OECD nations (Organisation for Economic Co-operation and Development [OECD], 2019, p. 70, and the 2022 PISA results stayed flat with over 50% below Level 1 in math (OECD, 2023, p. 16). The same class gradient appears in mathematics, but with even greater consequences since math performance is the primary gatekeeper for STEM tracks. Consequently, class position as indicated by SES predicts STEM outcomes more strongly: students who enter STEM tracks in senior high school are quite likely to be those who already have the material and other cultural resources before they started school.

Let us explore the evidence more fully. The statistical record shows that “prior achievement” is the best proximal predictor of academic success, but it is a predictor that correlates very strongly with class and ethnicity. Studies using Philippine data find that parental education and household SES shape achievement through access to materials, tutoring, and parental involvement (Cordero et al., 2022, pp. 8-9). Thus, public school students consistently underperform compared to their private school counterparts, the type of school being a good proxy for SES (Cordero et al., 2022, p. 11). The expectation that non-cognitive traits like grit or growth mindset can compensate for the disadvantage breaks down here since research on PISA 2018 PH data found growth mindset predicted learning only for higher SES students, and had no significant effect for lower SES students (Bernardo 2021, pp. 214-215).

The situation is most likely to be more pronounced for Indigenous learners in the Philippines. Indigenous students face the same class disadvantage but compounded by language barriers, remote and under resourced schools, and cultural exclusion from the science curriculum (Department of Education, 2015, pp. 2-3; Episcopal Commission on Indigenous Peoples, 2008, pp. 9-10). National PISA data does not disaggregate by ethnicity, but indigenous communities are overwhelmingly low-SES and rural, and local studies show Grade 6 IP learners in Palawan and Dumagat students in Nueva Ecija/Aurora have not met expected science/math competencies (Idulog et al., 2023, pp. 4-5). With only 0.4% of all Grade 12 Filipino students proficient in science by EDCOM 2’s 2024 data, Indigenous learners sit at the lowest end of an already steep SES gradient (Second Congressional Commission on Education [EDCOM 2], 2024, p. 23).

This has obvious consequences for higher education. Evidence for middle-class overrepresentation in SUCs is strong, though perhaps strongest in institutions like UP, where many future scientists come from. A 2019 UP CIDS survey of 3,800 UP students found only 14.3% came from the bottom 40% of households, while 60.1% came from the top 20% (Reyes et al., 2019, p. 6). When free tertiary education began in 2017, SUC enrollment was largely middle class. PIDS modeling using pre-2017 PSA data estimated that free tuition subsidies would flow disproportionately to the richest 40% of students versus the poorest 40%, showing SUC enrollees at baseline were not majority poor (Reyes et al., 2017, p. 12). CHED’s 2018 prioritization policy further confirmed this by reserving slots for 4Ps and Listahanan beneficiaries because “free tuition alone” would subsidize students who already passed admission filters tied to SES (Reyes et al., 2017, p. 12; Second Congressional Commission on Education, 2024, p. 158-159).

Indigenous learners are, of course, severely underrepresented in higher education, including SUCs. National data does not disaggregate enrollment by ethnicity, but proxy evidence shows the gap is stark. DepEd and EDCOM 2 (2024) data indicate IP communities are overwhelmingly rural, low-SES, and have lower SHS completion rates. EDCOM 2 also notes that proficiency gaps are “even more severe in structurally disadvantaged school settings… GIDA and last mile schools” where many indigenous communities are located (pp. 150-151). RA 10931 may have removed tuition, but certainly not the academic filters that convert class advantage into access (Reyes, et. al., 2017, p. 12).

Habitus, cultural capital, and codes

Allow me to discuss how we might proceed to frame this theoretically. Pierre Bourdieu’s theory of cultural reproduction holds that schools appear neutral but they, in fact, reward the capabilities and resources already possessed by the middle and upper classes (Bourdieu, 1986). This is what “prior achievement” amounts to. Science in the Philippines is elitist because the education system functions to convert existing class advantage into academic and scientific credentials, even as it marginalizes alternative knowledge systems to the disadvantage of indigenous communities.

Two important concepts are deployed by Bourdieu to explain class advantage: habitus and cultural capital. Habitus and cultural capital are distinct but interwoven in Bourdieu’s theory. Habitus refers to internalized habits and dispositions (evidenced by a “feel for the game”) that are shaped by one’s social environment, while cultural capital denotes the knowledge, skills, credentials, and tastes that hold value in specific fields such as education. They overlap most clearly in embodied cultural capital, where resources such as command of the academic language or confidence in the classroom setting are part of the habitus, and thus appear natural. Habitus explains how people perceive and act, whereas cultural capital explains what resources they can mobilize for advantage. Together, they show how inequality is reproduced: the habitus associated with the dominant class generates practices that align with the cultural capital schools reward, making social advantage appear as individual merit (Bourdieu, 1986, pp. 242-243, 248).

When I handled graduate courses at the UP College of Education, I made it a point to ask my students who were secondary education in-service teachers and administrators this question: in your schools, in which section are you likely to find students from affluent or middle class backgrounds? The answers, without exception, are always the top section. Unfortunately, a few poor students who make it to this section or, even more dramatically, that single student from an impoverished family who graduates with top honors is enough to distract many from the pattern staring us in the face. For every poor student who succeeds, how many hundreds of others fail? This is an exception that proves the rule.

Basil Bernstein’s theory of codes provides another way to frame this demonstrable link between SES and the learning that happens in classrooms (Bernstein, 1971). Most subject areas in formal schooling operate almost entirely on the basis of what he called an elaborated code — abstract, explicit, and decontextualized language that form part of established academic norms. Students from working class and indigenous backgrounds, on the other hand, are often socialized in a different, restricted code or in oral, community-embedded knowledge traditions that do not align with school expectations (Bernstein, 1971, p. 76). If schools do not explicitly teach or help students switch from the restricted (and context-dependent) code to the elaborated code, education effectively becomes a barrier rather than a ladder.

Allow me to illustrate this with a real-world example. One of my graduate students at the College Education who taught high school math once shared the case of a student who was failing in math. She found out that the student, who comes from a very poor family, was a street vendor. As a vendor, he was quite quick and agile at making calculations. In the streets, the numbers made sense and carried real consequences. In the classroom, however, confronted with abstract mathematical concepts, he was lost and, indeed, quickly lost interest in the lessons.

Bernstein’s concepts of strong classification and framing are also relevant here: science maintains tight boundaries between disciplines and leaves control of content and evaluation in the hands of insiders (Bernstein, 1971, pp. 47-55). This has meant not only the privileging of cultural resources associated with the middle and upper class students but also the systematic delegitimization of indigenous knowledge systems—such as traditional ecological knowledge, indigenous health practices, and community-based agricultural methods—which are classified as “non-scientific” and excluded from the formal curriculum (Department of Education, 2015, pp. 3, 5-6).

Indeed, indigenous learners face additional marginalization: they are more likely to attend under-resourced schools, experience instruction in a language they do not speak at home, and encounter a curriculum that renders their own knowledge invisible (Idulog et al., 2023, pp. 4-5). This illustrates Bourdieu’s point about the illusion of meritocracy in formal education: the system selects on characteristics that look like individual ability but are in fact the sediment of class and cultural advantage (Bourdieu, 1986, pp. 248-249).

Clearly, the claim that education is the great equalizer fails in the Philippines, and exclusion in science is an integral part of this failure. Science is elitist in terms of access where participation is restricted because SES and cultural background determine who acquires the prior achievement needed to enter scientific training; in language, because science demands the elaborated code of the dominant class (Bernstein, 1971, p. 76); and in epistemology, because indigenous knowledge systems are excluded by strong classification and framing (Bernstein, 1971, pp. 47-55). Far from neutralizing differences, the system sorts students by them and then legitimizes the outcome as merit. Education does not function as the great equalizer but, rather, as the great barrier.

Conclusion: Implications and Ways Forward

The problem of exclusion in education is the same problem of exclusion in science, writ small. If science remains tied to the codes, credentials, and epistemologies of the dominant class, it will continue to reproduce inequality rather than challenge it. The implication is that improving Philippine science education requires more than raising test scores. It demands changing what counts as legitimate scientific knowledge and who gets to participate in its production and consumption, and everything else that these require.

Three directions matter. First, pedagogical code-switching needs to be explicit. Schools should teach the language of formal learning and science as a second discourse, without devaluing students’ home language and reasoning practices. Bridging activities that move from community-based problems to formal scientific models can make the transition less abrupt. Second, curriculum classification and framing should be loosened to recognize indigenous and local knowledge systems. Integrating traditional ecological knowledge, community health practices, and indigenous agricultural methods into science subjects would expand the epistemic base and give marginalized students entry points where their own habitus is an asset, not a deficit.

One example of an approach that addresses the problem of classification and framing is ethnomathematics. Ethnomathematics is the study of how cultural groups develop mathematical ideas in daily life — like “banig” weaving patterns or farming ratios (D’Ambrosio, 1985, p. 44; Alangui, 2010, pp. 96-98). This can constitute an effective response to the problem described by Bernstein where strong classification keeps school math separate from indigenous knowledge, while strong framing lets teachers control what “counts” as legitimate math using the dominant class language (Bernstein, 1971, pp. 47-55). Ethnomathematics weakens both by integrating community practices into STEM lessons and letting students’ contexts shape instruction. This creates a cognitive bridge to formal concepts and increases engagement, as the existing IPEd program does in Ifugao (Nangpuhan, 2021, pp. 17-20). While it does not solve the problem of poverty or resource gaps, it counters epistemic marginalization by affirming that Indigenous knowledge belongs in STEM classrooms.

Third and last, there is a need to address material conditions alongside cultural ones. Since SES explains a larger share of variance in the Philippines than in most OECD countries (OECD, 2019, p. 71), interventions must reduce the dependence of achievement on household resources. This means better-resourced public schools, targeted support for low-SES learners, and teacher training that recognizes how class and culture shape classroom interaction.

None of these erase standards of scientific rigor. But rigor without inclusion inevitably turns science into a gatekeeping device. A more plural and responsive science education would make the field less elitist and more capable of addressing the problems that actually matter in the Philippine context. Only then does the claim that education equalizes become more than empty, if not deceptive, rhetoric.

Bibliography

Alangui, W. V. (2010). Ethnomathematics and culturally relevant mathematics education in the Philippines. The Mathematics Educator, 13 (2), 17–29. https://doi.org/10.1142/S1793395522100059

Bernardo, A. B. I. (2021). Socioeconomic status moderates the relationship between growth mindset and learning in mathematics and science. Evidence from PISA 2018 Philippine data. International Journal of School & Educational Psychology, 9(2), 208-222.

Bernstein, B. (1971). Class, codes and control: Vol. 1. Theoretical studies towards a sociology of language. Routledge & Kegan Paul.

Bourdieu, P. (1986). The forms of capital. In J. G. Richardson (Ed.), Handbook of theory and research for the sociology of education (241–258). Greenwood Press.

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Nangpuhan, D. G. (2021). Surfacing the praxis in curriculum indigenization by mathematics teachers of public secondary schools in Ifugao, Philippines. IAFOR Journal of Education, 9_(3), 51–66. https://doi.org/10.22492/ije.9.3.03

Organisation for Economic Co-operation and Development. (2019). PISA 2018 results (Volume II): Where all students can succeed. OECD Publishing. https://doi.org/10.1787/b5fd1b8f-en

Organisation for Economic Co-operation and Development. (2023). PISA 2022 results (Volume I): The state of learning and equity in education. OECD Publishing. https://doi.org/10.1787/53f23881-en

Philippine Daily Inquirer. (2023, December 5). PH students still among lowest scorers in reading, math, science PISA. Inquirer.net. https://newsinfo.inquirer.net/1863028/ph-students-still-among-lowest-scorers-in-reading-math-science-pisa

Reyes, J. I., Albert, J. R. G., Tabuga, A. D., Quimba, F. M. A., & Almeda, M. V. (2017). Who will benefit from the free tuition law? Rappler. https://www.rappler.com/voices/thought-leaders/173203-who-will-benefit-free-tuition-law/

Reyes, J. I., Albert, J. R. G., Tabuga, A. D., Quimba, F. M. A., & Almeda, M. V. (2019). Who benefits from free tuition? Evidence from the University of the Philippines (UP CIDS Discussion Paper 2019-03). UP Center for Integrative and Development Studies. https://cids.up.edu.ph/who-benefits-from-free-tuition-evidence-from-the-university-of-the-philippines/

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